Social scientists of mixed-methods research have traditionally used human annotators to classify texts according to some predefined knowledge. The “big data” revolution, the fast growth of digitized texts in recent years brings new opportunities but also new challenges. In our research project, we aim to examine the potential for natural language processing (NLP) techniques to understand the individual framing of depression in online forums. In this paper, we introduce a part of this project experimenting with NLP classification (supervised machine learning) method, which is capable of classifying large digital corpora according to various discourses on depression. Our question was whether an automated method can be applied to sociological problems outside the scope of hermeneutically more trivial business applications. The present article introduces our learning path from the difficulties of human annotation to the hermeneutic limitations of algorithmic NLP methods. We faced our first failure when we experienced significant inter-annotator disagreement. In response to the failure, we moved to the strategy of intersubjective hermeneutics (interpretation through consensus). The second failure arose because we expected the machine to effectively learn from the human-annotated sample despite its hermeneutic limitations. The machine learning seemed to work appropriately in predicting bio-medical and psychological framing, but it failed in case of sociological framing. These results show that the sociological discourse about depression is not as well founded as the biomedical and the psychological discourses—a conclusion which requires further empirical study in the future. An increasing part of machine learning solution is based on human annotation of semantic interpretation tasks, and such human-machine interactions will probably define many more applications in the future. Our paper shows the hermeneutic limitations of “big data” text analytics in the social sciences, and highlights the need for a better understanding of the use of annotated textual data and the annotation process itself.
Despite its undisputed importance, fear is yet to become a distinct research area for social theory. However, without a clear conceptualization of fear, the explanation of significant phenomena, such as the risk-related anxiety or the conflict of the global and the local, remains incomplete. This article aims at reintroducing fear at the fundamental level of social integration. First, the social contract theories of Hobbes and Rousseau are reinterpreted in order to identify a negative (based on fear) and a positive (based on hope) motivational basis of self-limiting one’s freedom of pursuing individual goals. These motivations for cooperation are the prerequisite of any society, as their absence results in disintegration. While social contract theories analyse them in detail, social theories forget about this level and focus on the mechanisms of action coordination. From the perspective of the two types of motivation for cooperation, two modalities of integration mechanisms identified by classical (Weber, Durkheim, Habermas) and late modern (Beck, Castells) social theories are elaborated. Based on such a model, the contemporary expansion of fear is explained as a consequence of the upset balance of the two modalities, leading to the predominance of negative integration.
This article aims at grounding critical theories with the help of psy discourses. Even if the relationship between the two disciplines has always been a controversial one, the article argues that therapeutic knowledge that accesses empirical forms of social suffering may offer important insights for critical theory. This general argument is demonstrated by complementing the theories of Bourdieu and Habermas with a clinical description of depression. First, the limitations of the capabilities of these influential theories in terms of how they can be used to conceptualize the variety of social suffering are introduced. Second, the psy discourses on depression are reviewed to identify and highlight latent references to the social. Third, by combining models of depressive suffering and various distortions of integration, an extended normative basis is elaborated. Instead of solely criticizing inequalities or distortions of communication, those social constellations are criticized that trap actors by producing a homogenous pattern of suffering.
This article examines and critically evaluates the processes of institutional memory transmission and political formation in post-socialist Hungary utilizing the critical theories of Habermas, Giddens and Bourdieu. In the first part of the article, a discourse analysis of the public debates about two distinctive 'lieux de mémoires'the House of Terror and the Holocaust Memorial Center -is elaborated. The concept of 'memory vacuum' is introduced to express the lack of minimal consensus between political actors about distinctive 20th-century Hungarian political traumas: the Holocaust and state socialist terror. In the second part of the article, focus groups conducted with high school visitors (n = 49) to these museums are analysed to explore the relationship between their interpretations of the past and evaluations of current political issues. In the final section of the article, an attempt is made to elaborate ideal typical patterns of collective memories and ensuing political cultures. It is concluded that the recent antidemocratic transformations in Hungarian political culture might be explained as a failure of both institutional and family transmission of collective memories to embed democratic principles.
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