2017
DOI: 10.5087/dad.2017.202
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Dialog Structure Through the Lens of Gender, Gender Environment, and Power

Abstract: Understanding how the social context of an interaction affects our dialog behavior is of great interest to social scientists who study human behavior, as well as to computer scientists who build automatic methods to infer those social contexts. In this paper, we study the interaction of power, gender, and dialog behavior in organizational interactions. In order to perform this study, we first construct the Gender Identified Enron Corpus of emails, in … Show more

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Cited by 7 publications
(5 citation statements)
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“…Furthermore, while automated sentiment analysis has spanned many areas (Pang and Lee 2008;Liu 2012) 3 analysis of power has been almost entirely limited to a dialog setting: how does person A talk to a higher-powered person B? (Gilbert 2012;Prabhakaran and Rambow 2017;Danescu-Niculescu-Mizil et al 2012). Here, we focus on a narrative setting: does the journalist portray person A or person B as more powerful?…”
Section: Introductionmentioning
confidence: 99%
“…Furthermore, while automated sentiment analysis has spanned many areas (Pang and Lee 2008;Liu 2012) 3 analysis of power has been almost entirely limited to a dialog setting: how does person A talk to a higher-powered person B? (Gilbert 2012;Prabhakaran and Rambow 2017;Danescu-Niculescu-Mizil et al 2012). Here, we focus on a narrative setting: does the journalist portray person A or person B as more powerful?…”
Section: Introductionmentioning
confidence: 99%
“…We isolate the first names using regular expressions, and follow Prabhakaran and Rambow (2017) to automatically assign gender and compute a gender ambiguity score taking into consideration: (1) the list of first names obtained based on Facebook profiles by Tang et al (2011); and (2) the Social Security Administration's (SSA) baby names data set. 2 The Facebook list has male and female assignment scores for each name, while the SSA maintains a data set of counts for baby names and gender for each year since the 1880s.…”
Section: Annotating Ptb For Gendermentioning
confidence: 99%
“…Eisenstein (2015); Eisenstein et al (2011);Nguyen et al (2015); Danescu-Niculescu-Mizil et al (2013); Jurafsky et al (2009)). Recently, also the possible interplay between social variables is considered (Prabhakaran and Rambow, 2017), but is mostly confined to age and gender (see e.g. Ardehaly and Culotta (2015); Argamon et al (2007); Barbieri (2008); Burger et al (2011);Eckert and McConnell-Ginet (2013); Holmes and Meyerhoff (2003); Hovy and Søgaard (2015); Nguyen et al (2014); Peersman et al (2011);Schwartz et al (2013); Wagner (2012)) as other social variables -such as social class -are not easily available (cf.…”
Section: Related Workmentioning
confidence: 99%