Classifying Party Affiliation from Political Speech

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Fightin' Words: Lexical Feature Selection and Evaluation for Identifying the Content of Political Conflict (2008, methodology): “For example, these word estimates might be used to train a classifier for uncoded documents (Yu et al. 2008), to scale future party manifestos against past ones (Laver et al. 2003), to scale individual legislators relative to their parties (Monroe and Maeda 2004), or to evaluate partisan bias in…”
User-level sentiment analysis incorporating social networks (2011, background): “There has been some previous work on automatically determining user-level opinion or ideology [2, 24, 27, 12, 7], generally looking at information just in the text that the users generate.”
Text Mining in Big Data Analytics (2020, background): “Moreover, nouns that hold no political connotations in common usage may come across as heavily-laden with political intentions when expressed in the context of a specific debate [8].”
Exploiting Social Network Structure for Person-to-Person Sentiment Analysis (2014, background): “This involves elements of work on modeling political afﬁliation (Agrawal et al., 2003; Mal-ouf and Mullen, 2008; Yu et al., 2008), bias (Yano et al., 2010; Recasens et al., 2013), and stance on debate topics (Thomas et al., 2006; Somasundaran and Wiebe, 2010; Lin et al., 2006; Anand et al., 2011),…”