Analyzing Political Rhetoric in Conservative and Liberal Weblogs Related to the Construction of the “Ground Zero Mosque”

Trait Associations for Hillary Clinton and Donald Trump in News Media

“…Bhatia (in press) has similarly applied this approach to study prejudice and stereotyping, as learned from news media (see also Lenton, Sedikides & Bruder, 2009 for a related insight). More relevant to the topic of this paper, Holtzman et al (2011) and Dehghani, Sagae, Sachdeva and Gratch (2014) have applied distributional models to study political bias in traditional news media and social media respectively, and Garten et al (2016) have recently used this approach to study morality-based representations in social networks. The ability of distributional models to approximate actual human semantic representations suggests that training these models on news media published during the 2016 U.S. presidential election could reveal key similarities and differences in representations and trait associations for the two candidates across different types of media outlets.…”

Quantifying Partisan Selective Exposure Through Network Text Analysis of Elite Political Blog Networks During the U.S. 2012 Presidential Election

“…Future studies are now encouraged to go beyond the headline to examine how these elite, partisan bloggers framed interpretations to select issues. Issue interpretations are often reduced to memes (Shifman, 2011), and future studies can employ such deeper text methodologies as topic modeling (Dehghani, Sagae, Sachdeva & Gratch, 2014;Grimmer, 2010) in the discovery of how these memes interact with partisanship to alter the framing or attribute agendas of public affairs issues as they are constructed for publics. Given that this study is limited by the 2012 U.S. electoral context, future studies should also go beyond heightened political times to assess the role of the political blog in diffusing partisan agendas on a day-to-day basis.…”

A Semantic Corpus Comparison Analysis of Couple‐Focused Interventions for Problematic Alcohol Use

“…Although, to our knowledge, this was the first study to explore semantic themes in psychosocial interventions using Wmatrix, other recent developments in automatic text analysis are gaining momentum in psychology. Topic models (or Latent Dirichlet Allocation, LDA; Griffiths & Steyvers, 2004) have recently gained popularity as a data-driven method for quantifying the semantic dimensions in texts and have recently been used to investigate, among other things, language patterns on Facebook and Twitter (e.g., Dehghani, Sagae, Sachdeva, & Gratch, 2014; Eichstaedt et al, 2015; Kern et al, 2014; Schwartz et al, 2013 ). In the clinical context, Atkins, Rubin, Steyvers, Doeden, and Baucom (2012) used topic models to empirically characterize common themes brought up in couple therapies for relationship distress, such as family, finances, and sex, as well as topics specific to different treatment modalities.…”