A New Method in Qualitative Research: The Continuously Customized Sociopolitical Analysis Model (CCSA)

 

 

 

Prof. Dr. Firuz Demir Yasamıs

ORCID: 0000-0002-8756-1366

 

 

ABSTRACT

Classical research methods applied in the analysis of social and political structures typically rely on fixed theoretical frameworks and predefined variables. However, conflict zones, multi-actor structures, and constantly changing power balances often render these methods insufficient for fully capturing social realities. This study introduces the Continuously Customized Sociopolitical Analysis Model (CCSA), developed to overcome such limitations, and illustrates its application through practical examples. The fundamental assumption of the model is that social and political structures are not static but process-oriented, dynamic, and too multilayered to be analyzed independently of their context. The model's analytical capacity is assessed through the case studies of Syria, Ukraine, Libya, and Turkey.

Keywords: Sociopolitical analysis, context sensitivity, CCSA MODEL, conflict analysis, social structure.

 

 

INTRODUCTION

Research methods used in the analysis of social and political structures are often shaped within the boundaries of specific historical and theoretical frameworks. However, in dynamic, multilayered, and continuously changing contexts, these rigid methods frequently fall short of accurately capturing reality. Particularly in conflict zones, where non-state actors rise to prominence, international interventions become constant, and local power balances are frequently reshaped, there is a growing need for more flexible and context-sensitive analytical approaches. This article introduces the "Continuously Customized Sociopolitical Analysis Model" (CCSA Model), developed by the author to address this methodological gap. Instead of relying on static and unchangeable analytical templates, the CCSA Model employs a continuously updated, multilayered analytical logic that dynamically reinterprets data offered by the context. The fundamental assumption of the model is that social and political structures derive meaning not from fixed variables but through processes, interactions, and contextual conditions. This study explains the theoretical foundations and application steps of the CCSA Model, exemplifies its analytical strength particularly through the Syrian case, and finally discusses its contribution to the social science literature.

Author used ChatGPT (OpenAI, GPT-4, 2025) to polish language and for stylistic suggestions. Author confirms that all intellectual content, analysis, and conclusions is his own.

Theoretical Foundations of the CCSA Model

In socio-political analysis processes, understanding the behavior of social structures and actors is usually achieved through specific theoretical frameworks. However, in complex and multi-actor environments like conflict zones, the inflexibility of these frameworks can limit the researcher’s ability to grasp social reality. The CCSA Model was designed to overcome this issue by synthesizing key approaches from existing social science literature.

The theoretical foundation of the model is built on three main intellectual pillars:

• Field Theory:
  Pierre Bourdieu’s field theory suggests that social structure is not a static entity, but rather a dynamic network of relations shaped by the positioning struggles of actors. The CCSA Model adopts the analysis of actors’ continuously changing positions within a context as a fundamental step. (Bourdieu, 1977)
• Process-Oriented Historical Analysis:
  Charles Tilly’s conceptualization of regimes and repertoires highlights the need to understand social change through a sequence of continuities and ruptures. Rather than freezing a given context into a single moment, the CCSA Model is grounded in the examination of transformation processes within the historical continuity of events. (Tilly, 2006)
• Comparative Case Study and Analytical Generalization:
  The case study method proposed by George and Bennett demonstrates that qualitative analyses are not limited to explaining specific cases but also allow for theoretical inference. Although the CCSA Model is specifically designed for each context, it is structured with the understanding that the findings emerging from these contexts can contribute to broader theoretical debates. (George & Bennett, 2005)

Built upon this theoretical foundation, the CCSA Model aims to provide the researcher with both contextual flexibility and analytical discipline. In doing so, the model offers a methodological framework that transcends classical models in the analysis of political arenas characterized by multiple actors, multiple scales, and constant change.

Some recent theoretical developments are also supporting the concept of CCSA Model. The first one is the process-tracing which is a qualitative research method used to investigate the causal mechanisms behind a particular phenomenon by closely examining the sequence of events or decisions over time. It is commonly used in political science, history, and sociology, particularly in studying complex processes and causal chains. (Beach ve Pedersen, 2019). The second theoretical contributions may come from Configurational Comparative Methods (CCMs), as developed by Charles Ragin, and later extended by Schneider and Wagemann. These are a set of research methods used to analyze complex causal relationships in social science, particularly in political science and sociology. These methods allow researchers to identify and analyze patterns of conditions (or configurations) that lead to specific outcomes. (Rihoux ve Ragin 2009). The third set of contribution to CCSA Model comes from Latour and friends’ work on ‘actor-network theory’. Actor-Network Theory (ANT), mainly developed by Bruno Latour is a theoretical and methodological approach in the social sciences that explores how social phenomena emerge from complex interactions between various human and non-human actors (referred to as "actants") within a network. ANT emphasizes that neither human agency nor the agency of non-human objects (like technology, institutions, or objects) can be understood in isolation. Instead, both are considered equally important in the creation and maintenance of social order. (Latour, 1996).

The core idea behind CCMs is that causal relationships in social phenomena are often complex and involve multiple factors interacting with one another. Rather than focusing on individual variables in isolation, CCMs examine how combinations of variables (or configurations) lead to particular outcomes.

METHOD OF CCSA

At the initial stage of the research process, the CCSA Model is positioned as a qualitative analytical framework. The model first constructs a foundation through qualitative data analyses in order to make sense of the socio-political dynamics, as well as the historical and cultural patterns offered by the context. This approach enables an in-depth examination of multi-actor networks in conflict zones, transformations in social identities, and local power structures.

Moreover, the model’s flexible structure allows the findings that emerge during the research process to be supported through quantitative analytical techniques. The integration of statistical methods — particularly time-series analysis — into the model enables qualitative findings to be tested and validated within broader patterns. This feature elevates the CCSA Model beyond rigid methodological divisions, transforming it into a mixed-methods analytical tool that maintains qualitative depth while offering opportunities for quantitative validation and generalization. In this way, the CCSA Model presents a holistic framework for research aimed at both understanding and explanation.

Data Sources in the CCSA MODEL

The CCSA Model is designed to allow for the integrated use of both qualitative and quantitative data. To adapt to the dynamic nature of field realities, the model places particular emphasis on diversity in data sources and on multi-source validation (or, triangulation).

Primary Data Sources

• Field Observations: Observing actor behaviors, interaction dynamics, and the unique conditions of the context during fieldwork.
• In-depth Interviews: Conducting unstructured or semi-structured interviews to explore the intentions, perceptions, and strategic preferences of actors.
• Focus Group Studies: Gathering collective perceptions and reactions from specific social groups or conflict parties.
• Official Documents: Government reports, agreements, protocols, parliamentary records, and documents from international organizations.

Secondary Data Sources

• Media and Press Monitoring: News agencies, newspapers, TV broadcasts, and independent journalism content.
• Academic Literature and Research Reports: Previous academic articles, field reports, intelligence reports, think-tank studies, and publications.
• Reports from International Organizations: Regular monitoring reports from institutions such as the UN, NATO, EU, International Committee of the Red Cross, International Organization for Migration, Human Rights Watch and Amnesty International.
• Databases: ACLED (Armed Conflict Location & Event Data Project), UCDP (Uppsala Conflict Data Program), SIPRI, World Bank, UNHCR statistics, and similar sources.

Social Media and Digital Sources

• Digital traces of actors (statements, videos, official accounts).
• Social media discourse analysis to track shifts in social perception.
• Digital maps: Conflict maps, event location maps.

Since the CCSA Model acknowledges that data will vary over time and that the positions of actors will be reinterpreted accordingly, it is built on the principle of continuous data updating. This feature distinguishes the model from static forms of analysis.

MODEL INTRODUCTION AND IMPLEMENTATION STEPS

The Continuously Customized Sociopolitical Analysis Model (CCSA) differs fundamentally from classical models of analysis in the social sciences, as it does not rely on fixed variables or predefined templates. Instead, it continuously updates its analytical steps in line with the internal dynamics of the research context, flexibly reshaping the model’s structure in response to the rhythm of field data.

The core logic of the model is based on the assumption that actors, events, and structures in the field are not static; rather, they are constantly interacting with one another, and this interaction can generate new equilibriums or disequilibrium at any moment. This approach requires the researcher to continuously revise both the theoretical framework and the logic of analysis according to the variability of data provided by the context.

Implementation Steps of the Model

Contextual Mapping:
In the first stage, the historical, geographical, cultural, and structural characteristics of the sociopolitical field under study are analyzed. This mapping provides the initial framework for describing the positions of actors and the existing network of relationships.

Dynamic Actor Analysis:
All actors within the context (states, organizations, political entities, social groups, and external intervening powers) are identified and analyzed in terms of their goals, tools, tactics, and current positions. As power balances shift, the model’s analytical map is regularly updated to reflect these changes.

Layered Process Analysis:
Events are evaluated not solely by their outcomes but also through the moments of rupture, continuity, and interaction within the process. Data at micro (interactions among individuals and small groups), mezzo (interactions at the level of communities and group structures), and macro (large-scale social structures and events at the national or global level) levels are analyzed simultaneously, focusing on how phenomena emerge across different scales.

Data-Driven Model Updating:
Every new finding obtained during the research process is used to reassess the model’s initial configuration, and when necessary, to update its variables. In this way, the analysis remains flexible and aligned with the evolving reality on the ground.

Context-Sensitive Theoretical Repositioning:
During the interpretation of data, the researcher refrains from applying an existing theoretical framework directly. Instead, the framework is re-examined and adjusted in light of the context’s unique characteristics. At this stage, the model favors interpretations that remain loyal to the distinctiveness of the context over those that aim for overly generalized analytical conclusions.

Thanks to these steps, the CCSA Model prevents the researcher from treating the field as a frozen snapshot; instead, it allows for the tracking of change, continuity, and ruptures within a coherent analytical logic.

Types of Research Questions and CCSA

CCSA is particularly suited for research questions that explore how political actors, parties, or interest groups shift their alliances, roles, or strategies over time, especially in politically fluid environments. This is relevant when studying coalition dynamics in parliamentary systems, analyzing party realignment, or understanding changes in political faction positions. Such environments demand real-time analysis of fluid political scenarios, where actors continuously adapt their behavior to new circumstances. This model is highly valuable for researching long-term social change and the shifts in political ideologies, values, and power structures within societies. It is particularly relevant when investigating how societies respond to external pressures like globalization, migration, technological innovations, or demographic shifts. These transformations often unfold in unpredictable ways and require a flexible, continuously customized approach to track and analyze evolving sociopolitical conditions. CCSA is effective for addressing questions around emergent conflicts or crises, such as wars, coup d’états political uprisings, regime changes, or governance crises. In these situations, political systems must rapidly adapt to shifting circumstances. Research that involves conflict management, post-crisis recovery, or responses to sudden political instability benefits from CCSA's real-time adaptation capabilities, helping to analyze how political systems and actors cope with and respond to emergent challenges. Another key strength of CCSA lies in examining how governments, international organizations, and political leaders adapt policies in response to changing political, economic, and social conditions. Research questions about adaptive policymaking in volatile environments, particularly during ongoing crises, pandemics, or geopolitical shifts, are well-suited for this model. It helps in understanding how decisions are made in real time based on rapidly changing data and circumstances. In the realm of cross-border and transnational studies, CCSA is highly effective for investigating issues that span multiple nations or regions, such as refugee flows, international trade, or global conflicts. These issues often involve a diverse set of actors with shifting priorities and alliances. CCSA allows researchers to track how sociopolitical factors evolve in a globalized context and how different political systems adapt to transnational challenges. CCSA is also valuable for analyzing the rise of populism, social movements, and grassroots political mobilization, particularly in response to social or economic grievances. It helps explore how these movements emerge, grow, and adapt in real-time, responding to shifts in public opinion, media narratives, or political opportunity structures. This makes it particularly useful for studying the evolving nature of populist movements in contemporary political landscapes. Research on electoral systems, voter behavior, and changing political landscapes can greatly benefit from the continuously customized approach of CCSA. In environments characterized by high volatility—such as electoral systems undergoing reform or shifting public opinion—CCSA enables real-time tracking of voter preferences, electoral outcomes, and the strategies political parties employ. It is especially useful for studying unpredictable electoral shifts and voter behavior in dynamic sociopolitical contexts.

In essence, CCSA is most useful for research questions involving complex, fluid, and dynamic sociopolitical systems, where traditional static analysis falls short. Its ability to adapt continuously to new data makes it invaluable for understanding sociopolitical change in real time.

Mega Work Example

Qadir and friends have shown an example of how big and related computer programs can be used for issues of humanity. Advances in electronics, computer programs (Apache Hadoop, NVivo or Spark), communication technology and the ability to process and analyze big data enables scientist to develop more reined assessment of the consequences of strong upheavals. (Qadir et al., 2016)

Kumar and Chindanur also gave another example for big data analysis through computer programs after 2012 US Presidential election. Social media has given new way of communication technology for people to share their opinions, interest, sentiments. Huge amount of unstructured data is generated from social media like Facebook, twitter, LinkedIn, which is repository of useful insights. Analytics can be applied to extract various useful insights form this. The research aimed to extract the knowledge from large social media data, identify the people sentiments and behavior to make cognizant decisions. These objectives are achieved by real time retrieval of twitter data and perform sentiment analysis. (Kumar et al, 2017).

APPLICATION EXAMPLE: THE SYRIAN CONTEXT

The Syrian civil war, as a conflict space characterized by multiple actors, multiple layers, and continuously shifting dynamics, offers an exceptionally suitable case for testing the applicability of the Continuously Customized Sociopolitical Analysis Model (CCSA).

From the very beginning of the conflict, the balance of power in Syria has been shaped not only by military parameters but also by international interventions, regional power struggles, tribal and sectarian affiliations, societal vulnerabilities, and micro-scale competitions among local actors.

When the Syrian context is analyzed within the framework of the CCSA Model, the analytical process is structured as follows:

Contextual Mapping:
The pre-conflict social structure of Syria (ethnic, sectarian, class-based, and tribal dimensions) and the authoritarian character of the political regime in its historical continuity were analyzed. The political power structure of the Ba'ath regime, the ethnic-sectarian-tribal composition of the military and security bureaucracy, and the patronage networks supported by the ruling elite formed the core elements of the mapping.

Dynamic Actor Analysis:
From the beginning of the civil war, all involved actors (the regime, opposition groups, the PYD, ISIS, Turkey, Iran, Russia, the United States, and the Gulf states) were identified, and their alliances, conflicts, and interest-based contradictions were updated periodically. Given that the positions of international actors often shifted within short timeframes, the logic of analysis was kept deliberately flexible.

Layered Process Analysis:
The analysis did not focus solely on the military trajectory of the conflict; instead, it also examined the collapse of Syria’s domestic political institutions, the social impact of refugee flows, the socio-economic fractures triggered by the conflict, and the reflections of these developments at the local, regional, and international levels.

Data-Driven Model Updating:
In light of field data, it became clear that the dynamics of the conflict needed to be re-examined with each new development. For example, Russia’s intervention in 2015 fundamentally altered the model’s calculations of the balance of power, necessitating a repositioning of Russia as a decisive actor in the analysis.

Context-Sensitive Theoretical Repositioning:
The Syrian civil war revealed the inadequacy of classical state-centric analytical approaches. Consequently, the sociopolitical positions of non-state actors—especially quasi-state structures and militia groups—were placed at the center of the theoretical model. The Syrian case thus demonstrated the increasing fluidity of the “state” concept and the emergence of a multi-actor "plurality of power centers."

This application within the Syrian context shows that the CCSA Model offers an analytical framework that is sensitive to changes on the ground, more faithful to empirical reality, and attentive to contextual particularities.

Comparison of the CCSA Model and Grounded Theory

There are similarities between the CCSA Model and the Grounded Theory; however, significant differences also exist between these two research approaches. The tables below outline these differences from various perspectives.

Table 1: Comparison between the CCSA Model and Grounded Theory Purpose and Scope of Application
CCSA Model	Grounded Theory
The CCSA Model is a practical framework developed to analyze the dynamic and context-dependent structure of socio-political phenomena. It is particularly suitable for political, historical, and cultural analyses.	Grounded Theory is a qualitative research method focused on theory generation. It aims to construct a conceptual framework grounded in empirical data collected from the field. It is commonly used in disciplines such as sociology, anthropology, education, and health sciences.

 

Table 2: Comparison between the CCSA Model and Grounded Theory Type of Approach
CCSA Model	Grounded Theory
Primarily operates through a balance of deductive and inductive reasoning. It refines and adapts existing theoretical knowledge through specialized analyses, thus contributing to theoretical development.	Employs a fully inductive approach. It avoids forming hypotheses before data collection and builds theory directly from the data.

 

Table 3: Comparison between the CCSA Model and Grounded Theory Sensitivity to Time and Context
CCSA Model	Grounded Theory
Pays particular attention to the historical, spatial, and temporal variability of socio-political contexts. The model allows for continuous updates and context-specific interpretations.	Is sensitive to context, but typically abstracts from patterns observed in the field. Historical variability and political fluctuations are often left outside the scope of the analysis.

 

Table 4: Comparison between the CCSA Model and Grounded Theory Contribution to Theory
CCSA Model	Grounded Theory
Rather than testing existing theories, it modifies and contextualizes theoretical frameworks to produce more accurate explanations.	Theory is not developed independently of the data; the core aim is to generate new theory directly from empirical data.

 

Table 5: Comparison between the CCSA Model and Grounded Theory Method of Application
CCSA Model	Grounded Theory
Follows a critical, comparative, and content-focused analysis process. Theoretical knowledge and field data continuously inform and refine each other throughout the research.	Follows a systematic coding process (open, axial, selective coding). The steps for moving from data to theory are clear and structured.

In summary, the CCSA Model is a flexible framework designed primarily for political analyses and the interpretation of social transformation processes, where theoretical frameworks are continuously revisited and refined in light of contextual changes. The Grounded Theory, by contrast, is a data-driven approach aimed at developing new theoretical frameworks from scratch, based on the empirical material collected during fieldwork. If the research goal is to derive a new conceptual framework from field data, the Grounded Theory is the more appropriate choice.

 

Table 6: Comparative Evaluation
	CCSA Model	Grounded Theory
Context Sensitivity	Extremely high. The core logic of the model is built upon producing analytical frameworks tailored to shifting contexts. Particularly useful in conflict zones, environments with unclear actors, and settings with fluid power dynamics.	Considers context, but since it is data-centered, context remains limited to what is captured within the data. It is less suited to rapidly adapting to fast-changing political situations.
Theory and Historical Framework	Customizes existing theories according to context and revises them as needed. Superior for examining the relationship between historical continuity and contemporary phenomena.	Prioritizes fidelity to the data before proposing any theoretical framework. Attempts to construct theory independently of pre-existing models, which may delay theory generation in dynamic political environments.
Actor-Relationship Analysis	Offers flexibility in analyzing changes in non-state actors, international interventions, and shifting local power balances. Well-suited for multi-layered actor mapping.	Defines actors and their relationships based on data. If these relationships are not sufficiently revealed in the data, the analysis may remain superficial.
Field of Application	Particularly strong in analyzing variable and fragile environments such as conflict regions, power vacuums, and complex alliances.	Particularly strong in sociological field studies, the systematic description of cultural practices, and the development of theory related to organizational structures.

Theoretical Conclusion

In conflict-ridden, multi-layered, multi-actor, and constantly shifting political contexts, the classical Grounded Theory approach may often prove inadequate due to the time loss inherent in the data collection and theory-building process, as well as the difficulties in adapting to rapidly changing dynamics. In contrast, the CCSA MODEL offers a more functional alternative for unstable political environments or conflict zones, as it allows for the continuous, context-sensitive updating of theoretical frameworks, enables actor analysis at both micro and macro levels in a manner synchronized with real-time developments, and facilitates the simultaneous observation of historical continuities and ruptures. While Grounded Theory focuses on deriving assumptions and hypotheses, the CCSA MODEL suggests context adaptation and the inclusion of an interpretative layer.

The Ukraine-Russia War and the Sociological Systems Framework: Transformations and Interactions of Social Structures

Beyond representing a global security crisis, the Ukraine-Russia War also symbolizes the transformation of social structures, collective identities, and interstate relations. Analyzing the war through the lens of the CCSA Model offers a deeper understanding of how social dynamics have evolved, the roles individuals and communities have assumed throughout the war, and the ways in which the social fabric has been reshaped. The CCSA Model provides a significant theoretical framework for understanding the interactions, interdependencies, crisis responses, and transformations of social systems during this process. From this perspective, the analysis of the social transformations triggered by the Ukraine-Russia War not only sheds light on the military and political dimensions of the conflict but also reveals the interactions between social structures and identities.

Social Structural Change and Identity Crises

The war has led to the formation of a deep national identity and enhanced social solidarity within Ukrainian society. Within the framework of the CCSA Model social structures are shaped not only by the state’s sovereignty but also by the collective consciousness and the sense of belonging among the people. The national unity that the Ukrainian population has developed in response to Russia’s aggression clearly illustrates the model’s emphasis on collective identity and social belonging. Social solidarity strengthened public motivation, particularly during the initial phases of the war, and contributed to reshaping Ukraine's internal structure. In this context, the war can be viewed as a “socio-political crisis” that transforms social structures.

On the other hand, Russia's claims of sovereignty over Ukraine reflect the CCSA Model’s conceptualization of social conflict and its role in shaping social structures. The polarization between pro-Russian and pro-Western groups within Ukraine has deepened social conflict and sharpened the opposing positions of distinct social systems. This conflict not only signals political tension but also heralds a broader cultural and social transformation. As a consequence of Russia’s intervention, social structures have exhibited tendencies either toward homogenization or polarization, while historical identities and the collective sense of national belonging have been reshaped.

Military Strategies and Social Interactions

From the perspective of the CCSA Model the military dimensions of the Ukraine-Russia War are also closely intertwined with social structures. Russia's military strategies have evolved in response to the crises within social systems. While Russia initially pursued more conventional military strategies in its assault on Ukraine, it gradually shifted toward hybrid warfare tactics. This shift can be understood not only as an attempt to exert military power but also as a strategy targeting the vulnerabilities of social systems. Cyberattacks and disinformation campaigns, in particular, have served as tools aimed at transforming and manipulating social structures. The war has played a critical role in shaping both the flow of information within societies and public perceptions.

Ukraine’s military defense strategies, on the other hand, have fostered a structure that reinforces national solidarity and unity. Western military assistance has become a key factor in shaping Ukraine’s defense strategies, enabling international actors to influence the country’s internal defense organization. As the war has progressed, the defense of Ukraine’s national identity and social structures has increasingly reinforced the social impact of the war’s military and strategic dimensions.

Social Crisis and the Human Rights Dimension

The humanitarian dimension of the war provides an important case for understanding, through the lens of the CCSA Model, how social systems evolve during periods of crisis and how these crises affect human rights. The millions of people fleeing Ukraine were not only in search of refuge but were also forced to confront questions surrounding their national identity and sense of social belonging. The responses of social structures to these refugee groups — including how these individuals would be positioned within established societies — have deepened the war’s social impact.

The refugee crisis has also prompted Western actors to reconsider their strategic approaches to Russia’s success in the conflict. While providing military assistance to Ukraine, Western states have faced significant challenges in resettling refugees and providing necessary social services. The acceptance and integration of migrants, within the framework of the CCSA Model illustrates how social systems organize in the face of crises, the effectiveness of these organizational responses, and the extent to which societies undergo transformation.

Interim Assessment of the Ukraine-Russia War

When analyzed through the lens of the CCSA Model the Ukraine-Russia War serves as a significant example that reveals the interaction and transformation of social systems. The war is not merely a military and diplomatic conflict but also an opportunity to understand how social structures, identities, and collective consciousness are shaped and reshaped. The Ukrainian people's response to the war, the transformation of national identity, and the ways in which the war reshapes social structures can be clarified using the core analytical tools of the CCSA Model. This process will contribute to our understanding of how social systems respond to crises and how wars reshape societies.

The Libyan Crisis and the Sociological Systems Framework: The Clash of Social Structures and State Collapse

The civil war and political conflicts in Libya represent more than just a military struggle; they symbolize a process in which social systems confront and interact with one another. The CCSA Model offers a robust theoretical framework for understanding the evolution of social structures in the face of crises and the strategies these structures employ to cope. The developments in Libya illustrate not only how social systems respond to conflict but also how such conflicts transform social structures.

State Collapse and the Transformation of Social Systems

The political collapse in Libya, which began with the civil war in 2011, presents an important example of state failure and the subsequent disintegration of social systems within the CCSA Model framework. The chaotic transitional period following the end of Gaddafi’s 42-year rule was one of the most profound ruptures affecting Libyan social structures. The collapse of the state led to the reconfiguration of all components of the social fabric and brought ethnic, sectarian, tribal, and clan-based affiliations to the forefront. From the perspective of the CCSA Model the loss of state sovereignty in Libya reactivated dormant collective identities. Historical tensions among Libya's various regional, ethnic, and sectarian groups deepened with the weakening of state authority, making the boundaries between social structures more pronounced. This process enables us to better understand how social systems react to crises and how their responses evolve. Different Libyan groups sought to fill the power vacuum by creating their own "social sub-systems," which in turn attempted to occupy the political space left vacant by the collapse of state authority.

Tribalism and Political Conflicts:

From the perspective of the CCSA Model ethnic, tribal, and clan-based structures in Libya played a decisive role throughout the war. Libya is a country characterized by an expansive tribal structure, and Gaddafi’s long rule had largely centralized these tribal systems. However, with the fall of the state, a new era emerged in which tribes and regional power centers reasserted themselves. This accelerated the transformation of Libya’s social fabric and triggered ethnically driven conflicts. Tribalism, within the framework of the CCSA Model appears as a key factor shaping the transformation of social systems. In order to defend their own interests, Libyan tribes formed armed groups, and following the disintegration of the state, a local struggle for power began. This struggle was not merely a military confrontation but also revealed the historical fractures in Libya’s social structures. Inter-tribal conflicts reshaped collective identities and senses of belonging, thereby deepening the social impact of the war.

International Intervention and the Shaping of Social Structures:

The civil war in Libya also offers a compelling example of international actors intervening in the dynamics of social structures, as understood through the CCSA Model. NATO’s intervention in 2011 accelerated the collapse of the Libyan state and transformed the conflict into an internationalized war. This intervention not only impacted the country’s military and political balances but also deeply affected the social structures within Libya. The various actors involved in the war sought to manipulate Libya’s social sub-systems to serve their strategic goals. Western states and regional powers played active roles in reshaping Libya's political and social landscape in line with their interests, which further diversified the conflict and added complexity to the country’s social systems. The CCSA Model interprets such interventions as external interactions between social structures. International interventions did not only generate military and political consequences but also reshaped Libya’s internal social dynamics and national sense of belonging. Regional, tribal, and clan-based conflicts—particularly between armed groups in Libya's east and west—were exacerbated by international intervention and the backing of external actors.

Migration and Human Rights - The Social Reflections of War:

The humanitarian dimension of the Libyan civil war represents a significant example of social crisis within the CCSA Model framework. The displacement of millions of Libyans and their forced migration due to the war illustrates yet another aspect of how Libya's social structure has been reshaped. These waves of migration created serious social problems not only in neighboring countries but also in Europe. Refugees and internally displaced persons emerged as a direct result of the disintegration of the Libyan state and the collapse of its social system. The mass exodus from Libya is a long-term indicator of the war’s and state collapse’s deep social effects. This process has led to power imbalances and identity shifts within social systems and has forced the international community to reconsider its policies toward refugees. The war did not only redraw physical borders but also complicated transitions across social boundaries and disrupted feelings of belonging.

Libya Interim Assessment: The Sociological Reflections of War

When analyzed through the CCSA Model the Libyan civil war reveals crucial dynamics such as the dissolution of social structures, the reformation of national identities, and the transformation of collective senses of belonging under crisis conditions. The collapse of the state and the international interventions reshaped Libya’s social structures, undermined national unity through tribal, ethnic, and regional conflicts, and amplified deep-rooted fractures in the country's social fabric. During this process, the evolution of social sub-systems was shaped by both state failure and the interventions of international actors. The Libyan crisis is not only a military confrontation but also a process that transformed social structures and forced a rethinking of identities and senses of belonging. Analyzing this process through the lens of the CCSA Model ensures a deeper understanding of the interaction between social structures and crises in Libya.

The Syrian Case (2011 and beyond): A CCSA Model Perspective

The Syrian civil war, which erupted in 2011, represents not only a military conflict but also a multi-layered process of social transformation. From the perspective of the CCSA Model the conflicts between social structures in Syria, the erosion of state sovereignty, and the resulting transformations in social systems deserve careful analysis. The Syrian civil war offers insight into how social sub-systems interact, how conflicts affect social structures, and how international interventions shape processes of social transformation.

The Collapse of the State and Transformation of Social Structures in Syria

The Syrian civil war, which began in 2011, serves as a poignant example of how the erosion of state sovereignty can lead to the transformation of social structures. The Assad regime's repressive response to protests, influenced by the Arab Spring, weakened the state's authority and initiated a process of social reconfiguration. As the state's control diminished, various religious, sectarian, and ethnic groups began redefining their identities and affiliations. This led to the fragmentation of Syria's demographic landscape into distinct social subsystems, each establishing its own power structures in the absence of a strong central government. From the perspective of the CCSA model, the state's collapse resulted in the disintegration of the overarching social system, empowering local groups and making the boundaries between different social structures more pronounced.​

Tribalism, Sectarianism, and Ethnic Conflicts in Syria

The onset of the Syrian civil war brought tribalism, sectarianism, and ethnic affiliations to the forefront of societal dynamics. Historically, Syria has been a mosaic of diverse groups, including Sunni Arabs, Shiite Arabs, Alawites, Kurds, and others. As state authority waned, these groups' identities became more pronounced, leading to increased tensions and conflicts. The Assad regime, predominantly Alawite, faced intensified sectarian strife with the Sunni majority. Simultaneously, Kurdish groups pursued greater autonomy, leading to clashes with both the regime and other factions. These developments underscore how, within the CCSA framework, the weakening of central authority can exacerbate divisions among societal subgroups, each vying to assert and protect its identity.​

International Intervention and Syria's Social Fabric

International involvement in Syria's civil war has significantly influenced the country's social structures. Support from Russia and Iran bolstered the Assad regime, while the United States and certain Western nations backed opposition forces. These external interventions altered internal power dynamics and deepened societal divisions. The emergence of terrorist groups like ISIS further complicated the situation, intertwining global geopolitical interests with local social fabrics. Such interventions have strained Syria's already fragile social subsystems, with international actors often reinforcing specific group identities, thereby intensifying internal conflicts.​

Migration, Human Rights and Societal Impacts of the War

The Syrian civil war has had profound implications for human rights and societal structures. Millions have been displaced, both internally and as refugees, reshaping the demographic and cultural landscapes of Syria and neighboring regions. This mass migration is not merely a physical movement but also a redefinition of identities and community affiliations. The war has deepened sectarian and ethnic divides, leading to significant human rights violations, including war crimes and systemic abuses. These developments highlight the vulnerability of social systems in the face of prolonged conflict and the challenges in preserving human rights amid such turmoil.​

Sociological Reflections on the Syrian Conflict

Analyzing the Syrian civil war through the CCSA Model reveals the intricate interplay between state authority, societal structures, and external influences. The collapse of central governance led to the emergence of localized power centers, each rooted in distinct identities and affiliations. International interventions further complicated these dynamics, often reinforcing divisions rather than fostering unity. The Syrian case exemplifies how prolonged conflict can fundamentally alter societal structures, leading to lasting transformations in identity, governance, and community cohesion.​

Turkey's Peace Process (2009–2015): A CCSA Perspective

Turkey's Kurdish issue has long been a source of societal and political tension. The peace process initiated in 2009 aimed to address these challenges by fostering dialogue between the Turkish state and the PKK. From a CCSA standpoint, this initiative sought to recalibrate the power dynamics between the state and Kurdish societal subsystems. However, the process also exposed deep-seated divisions and competing narratives of identity and belonging within Turkish society. The state's engagement with the PKK challenged traditional notions of sovereignty and highlighted the complexities of integrating marginalized groups into the national fabric.​

State Authority and Competing Social Subsystems

The peace process represented an attempt to redefine the Turkish state's relationship with its Kurdish population. By engaging in negotiations, the state acknowledged the PKK's influence and the need for a political solution. This move aimed to restructure the state's authority and address the grievances of Kurdish communities. However, the process also intensified identity politics, with various groups asserting their narratives and challenging the state's traditional power structures. The interplay between state authority and societal subsystems became a focal point of the peace process, revealing the complexities of governance in a diverse society.​

Impact on Identity and Belonging

The peace process had significant implications for identity and belonging within Turkey. For many Kurds, it offered hope for recognition and integration. However, it also sparked resistance among segments of the Turkish population who viewed the process as a threat to national unity. This tension underscored the challenges of reconciling diverse identities within a singular national framework. The process highlighted the fluidity of identity and the importance of inclusive policies in fostering societal cohesion.​

Rise of the Kurdish Movement and State Response

While the peace process aimed to integrate Kurdish voices into the political mainstream, it also witnessed the strengthening of Kurdish movements. The state's response to these developments was marked by caution and, at times, repression. The balance between accommodating Kurdish aspirations and maintaining national unity proved delicate. The state's strategies, influenced by both domestic pressures and geopolitical considerations, ultimately impacted the trajectory of the peace process and the broader dynamics of Turkish society.

The Role of International Factors

The Peace Process was not solely shaped by domestic dynamics within Turkey; international factors also played a significant role in influencing the course of the process. The PKK's growing strength, particularly in Northern Iraq, has clearly demonstrated how regional actors affected the Kurdish movement within Turkey. Moreover, the support extended to the Kurdish movement by Western powers such as the United States and the European Union further complicated the strategies of both Turkish societal subsystems and the state. The involvement of international actors, alongside the political and territorial influence of Kurdish nationalism and the PKK—especially in Syria—largely shaped the evolution of the peace process. Turkey, on one hand, sought to challenge the PKK’s international political legitimacy, while on the other, found itself compelled to take steps toward recognizing the political and cultural rights of the Kurds.

Interim Assessment of Turkey: Sociological Reflections of the Peace Process

Within the framework of the CCSA Model, the Peace Process represents a significant case study for understanding the transformation of social structures in Turkey. The process, which weakened the state’s sovereign power and led to the prominence of social identities, resulted in deep-rooted identity conflicts within society. The Kurdish identity, historically marginalized, played a pivotal role in reshaping the social fabric. Furthermore, the failure of the Peace Process can be attributed to the power imbalances between societal subsystems and the state's inconsistent policies. The tension between senses of belonging created a major arena of conflict between Kurdish demands and the resistance of the Turkish societal majority. Although the weakening of state authority offered an opportunity for restructuring the social order, the failure of the peace process ultimately prevented this opportunity from being realized.

Theoretical and Methodological Evaluation of Time Series Analysis within the Context of the CCSA Model

The dynamic nature of social and political phenomena clearly reveals the inadequacy of limiting research methodologies to linear causal models. Particularly in complex social cases such as conflict processes, the phenomena are shaped by multidimensional and multivariate structures, which fluctuate over time and vary according to conjunctural conditions.

In this context, the Continuous Customized Sociopolitical Analysis Model (CCSA Model) argues that social phenomena cannot be comprehended through singular and direct causal explanations. On the contrary, it posits that phenomena only become meaningful through the interaction of multiple variables within their historical, structural, and temporal contexts. The CCSA Model offers both a theoretical and methodological foundation for analyzing social phenomena characterized by multiple causalities. However, since the model assumes that causal relationships are temporally variable and dynamic, it requires an appropriate measurement and modeling tool during the analysis process. At this point, Time Series Analysis stands out as a suitable method for examining the multi-causal and effect-driven relationships within the CCSA Model framework, as well as for identifying the delayed effects on the development trajectories of events (Broomhead and Jones, 1989).

The time series method allows researchers to demonstrate how a particular social phenomenon evolves over time through changing parameters, which variables gain or lose significance throughout the process, and which factors fade away entirely. In doing so, the multi-causal structure theoretically defined by the CCSA Model can be empirically validated, and the temporal breaking points within the causal chain can be concretely analyzed. In fact, the analysis of dynamic social phenomena such as conflict processes clearly illustrates the necessity of this methodological integration. Cases such as the Russia-Ukraine War, the Libyan Civil War, the Syrian Civil War, and Turkey’s Peace Process all exhibit a conflict dynamic that unfolds over time, based on the interaction of multiple actors, variables, and strategies. In each case, the intensity, flow, and outcomes of the conflict were shaped not only by structural and instantaneous causes but also by the changing effects of these causes over time. Therefore, the combination of the CCSA Model approach with time series analysis offers a robust theoretical-methodological framework for analyzing conflict processes in the social sciences in a more holistic, process-oriented, and dynamic manner.

ANALYSIS OF CONFLICT DYNAMICS IN THE CONTEXT OF TIME SERIES APPROACH

Contemporary conflicts, both at the international and national levels, rarely unfold within a static framework. Instead, they evolve through dynamic processes that shift and transform over time. Understanding the onset, intensity, continuity, and resolution of conflicts, therefore, cannot be achieved through a mere “snapshot” of events, but rather through the examination of a sequential series of developments. In this regard, developing a research method grounded in time series analysis offers a critical contribution to comprehending the complexity and evolution of conflict processes.

The time series approach enables the chronological analysis of events within a structured temporal order, allowing researchers to identify distinct phases of a conflict and to pinpoint its critical turning points. Through this lens, conflicts occurring in diverse geographies — such as the Russia-Ukraine War, the Libyan Civil War, the Syrian Civil War, and Turkey’s Peace Process — can be examined within a unified analytical framework.

Case Study: Turkey’s Peace Process

The so-called Peace Process in Turkey, which aimed to halt the armed conflict between the PKK and the Turkish state, can be temporally divided into distinct phases. Each phase — including the initiation of the process, periods of negotiation, ceasefire declarations, political messaging to the public, and the process’s eventual collapse — can be systematically measured from a time series perspective through indicators such as the frequency of attacks, civilian casualties, border violations, and shifts in political discourse.

In this context, variables like conflict frequency and political statements serve as functional analytical tools for understanding the stability or crisis periods within the process. For example, the significant decline in the number of clashes observed between 2013 and 2015, and the abrupt surge following July 2015, provide concrete data for assessing the sustainability of the process and the dynamics behind its failure.

Case Study: The Syrian Civil War

In the case of the Syrian Civil War, the time series method can be employed to analyze the relationship between refugee flows, the intensity of armed conflicts, and the timing of international interventions. During the early stages of the war, the conflict was largely confined to local engagements. However, following Russia’s military intervention in the autumn of 2015, the conflict escalated into an international confrontation. The sharp increase in refugee flows during the same period demonstrates that this turning point generated not only military but also significant demographic consequences.

This structural shift created a clear trend break in the time series, indicating a transformation of the conflict beyond the dimension of violence, extending into international politics and humanitarian crises.

Case Study: The Russia-Ukraine War

In the case of the Russia-Ukraine War, the 2014 annexation of Crimea and the large-scale invasion attempt in February 2022 represent two major turning points. These two events triggered dramatic escalations in both the scale and intensity of the conflict, leading to the imposition of international sanctions, accelerated military deployments, and sudden shifts in geopolitical discourse.

From a time series perspective, these dates mark structural shifts, reflecting not only spatial but also strategic changes in the parameters of the conflict.

Case Study: The Libyan Civil War

In the Libyan Civil War, the intermittent nature of armed clashes and the periodic implementation of ceasefire agreements can be chronologically monitored through time series analysis. Periods of decreased conflict intensity, often following UN-backed negotiations, as well as phases of operational escalation — such as the siege of Tripoli by Haftar’s forces — can be systematically analyzed using the historical comparison capacity provided by this method.

Time series analysis enables the study of conflicts and resolution processes within a temporal continuum, allowing for the objective identification of turning points and structural transformations. This approach facilitates the empirical assessment of conflict dynamics based not solely on political discourse but on observable variables. By emphasizing that conflicts unfold in a sequential, dynamic, and interactive process rather than as isolated incidents, the method offers a significant methodological contribution to the literature on conflict studies.

Limitations of the Study

The Continuously Customized Sociopolitical Analysis Model (CCSA) developed in this study offers a flexible methodological framework that allows for the multilayered, dynamic, and context-sensitive analysis of social and political structures. However, like any research model, the CCSA Model has certain limitations.

First, the model’s core assumption of continuous data updating may pose challenges in field research, particularly due to constraints of time, resources, and accessibility. In conflict zones — where access to reliable data is often restricted, information flow is controlled or manipulated — the analytical capacity of the model is directly dependent on the quality and accuracy of the available data.

Second, the model’s focus on context-specific interpretation can limit the generalizability of its findings. While the CCSA Model is particularly effective at producing high-resolution analyses within specific contexts, the universal validity of its conclusions may be limited when applied beyond the original setting.

Third, the model’s requirement for the constant reassessment of its theoretical framework may challenge the methodological consistency of the researcher. This may complicate the model’s practical application for less experienced researchers and could jeopardize the continuity of the analysis.

Lastly, the model’s proposed mixed-method approach — the integration of both qualitative and quantitative data — may not always be feasible in every research environment. Particularly in conflict zones, the lack of sufficient and reliable quantitative datasets may limit the model’s ability to fully realize its comprehensive analytical potential.

Suggestions for Future Research

While the CCSA Model offers a significant theoretical and methodological contribution to the analysis of conflictual and multi-actor sociopolitical contexts, testing and further developing the model across different fields remains a critical need for future research.

First, testing the model through long-term comparative case studies will strengthen both the theoretical framework’s robustness and the model’s generalizability. Sample-based research conducted in different geographical, cultural, and political contexts will help clarify the model’s level of flexibility and its practical limitations.

Second, integrating the CCSA Model with time-series analysis could facilitate a more objective and measurable understanding of the dynamic nature of conflict processes. In this regard, supplementing the model with big data analytics and AI-assisted methodologies may enable a more systematic tracking of sociopolitical variables over time.

Third, testing the model within practical policymaking domains — including policymakers, civil society organizations, and international institutions — would reveal its potential to create tangible impacts beyond the academic world.

Finally, the interdisciplinary integration of the CCSA Model — for instance, in conjunction with political science, international relations, sociology, history, media studies, and AI-based data science — will enhance its applicability and contribute to methodological diversity within the social sciences.

CONCLUSION

The Continuously Customized Sociopolitical Analysis Model (CCSA) is an alternative research framework to classical analysis methods in the social sciences. It is designed to be flexible and context-sensitive. The model is built on the fundamental assumption that social and political structures are not static, but rather in a state of constant change, interaction, and transformation. From this perspective, analysis efforts constrained by fixed theoretical templates or rigid analytical frameworks are likely to fall short, particularly in conflict or crisis environments.

The CCSA Model compels researchers to approach field events not merely as isolated outcomes, but as products of dynamic processes, reciprocal interactions, and multi-layered power struggles. The model offers the flexibility to update its analytical framework in light of new data acquired at each stage of research. In doing so, it makes it possible to produce a context-specific and field-sensitive understanding, rather than a dogmatic analysis in the face of evolving realities.

As demonstrated in the case of Syria, in complex, multi-actor, and multi-layered crisis situations, the CCSA Model enables the simultaneous analysis of not only the visible dimensions of events but also the underlying structural dynamics, cycles of alliance and conflict between actors, socio-economic fractures, and the influences of the international system.

The model's contribution to the methodology literature lies in its ability to transcend static approaches in social science analysis by placing contextual variability and continuity at the center of the research process. It fosters an analytical logic that is flexible, field-sensitive, and conceptually critical.

The CCSA Model offers a context-sensitive and flexible tool for understanding conflict processes, power dynamics, and the transformation of social structures in the social sciences. Unlike fixed-variable approaches, the CCSA Model provides researchers with an analytical framework that can adapt to the shifting realities of the field. The model highlights the process-oriented nature of social structures and emphasizes the continuous reshaping of power balances through inter-actor relationships. By increasing methodological flexibility in social science research, especially in conflict-prone regions, the CCSA Model holds the potential to bridge the gap between theory and field data. In this regard, it is expected to make meaningful contributions to the social sciences and research methodology literature on both experimental and theoretical levels.

 

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