Sociological Applications of Topic Extraction Techniques: Two Case Studies

Abstract

Limited research has been conducted with regards to the applicability of topic extraction techniques in Sociology. Addressing the modern methodological opportunities, and responding to the skepticism with regards to the absence of theoretical foundations supporting the use of text analytics, I argue that Latent Semantic Analysis (LSA), complemented by other text analysis techniques and multivariate techniques, can constitute a unique hybrid method that can facilitate the sociological interpretations of web-based textual data. To illustrate the applicability of the hybrid technique, I developed two case studies. My first case study is associated with the Sociology of media. It focuses on the topic extraction and sentiment polarization among partisan texts posted on two major news sites. I find evidence of highly polarized opinions on comments posted on the Huffington Post and the Daily Caller. The highest polarizing topic was associated with a commentator’s reference on Hoodies in the context of the Trayvon Martin’s incident. My findings support contemporary research suggesting that media pundits frequently use tactics of outrage to provoke polarization of public opinion. My second case study contributes to the research domain of the Sociology of knowledge. The hybrid method revealed evidence of topical divides and topical “bridges” in the intellectual landscape of the British and the American sociological journals. My findings confirm the theoretical assertions describing Sociology as a fractured field, and partially support the existence of more globalized topics in the discipline.

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