User Demographics and Language in an Implicit Social Network

By Katja Filippova. 2012

68 citations recorded by the source corpus.

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Citations in the corpus

Returning the N to NLP: Towards Contextually Personalized Classification Models (2020, background): “…the above-listed experiments have been conducted on Twitter, a variety of other datasets have been used, including phone conversations (Mairesse et al., 2007; Ivanov et al., 2011), blogs (Mukherjee and Liu, 2010; Schler et al., 2006), Facebook (Markovikj et al., 2013), or YouTube (Filippova, 2012).”
External validity of sentiment mining reports: Can current methods identify demographic biases, event biases, and manipulation of reviews? (2014, unknown): “The list of papers found is here: [12,14–17,26,28,31–35,43–60].”
Computational Sociolinguistics: A Survey (2016, methodology): “Besides blogs and Twitter, other web sources have been explored, including LinkedIn (Kokkos and Tzouramanis 2014), IMDb (Otterbacher 2010), YouTube (Filippova 2012), e-mails (Corney et al. 2002), a Belgian social network site (Peersman, Daelemans, and Vaerenbergh 2011) and Facebook (Rao et al.…”
Semi-supervised Gender Classification with Joint Textual and Social Modeling (2016, background): “As for supervised learning, gender classification has been extensively studied in several textual styles, such as Blog (Nowson and Oberlander, 2006; Peersman et al. , 2011; Gianfortoni et al. , 2011), E-mail (Mohanmad et al. , 2011), YouTube (Filippova, 2012) and Micro-blog (Rao et al. , 2010; Liu e”
Why Gender and Age Prediction from Tweets is Hard: Lessons from a Crowdsourcing Experiment (2014, background): “A variety of datasets have been used, including Twitter (Rao et al., 2010; Bamman et al., 2014; Fink et al., 2012; Bergsma and Van Durme, 2013; Burger et al., 2011), blogs (Mukherjee and Liu, 2010; Schler et al., 2005), telephone conversations (Garera and Yarowsky, 2009), YouTube (Filippova, 2012) a”
User Classification with Multiple Textual Perspectives (2016, background): “User gender classification has been extensively studied in several domains, such as Blog (Peersman et al., 2011; Gianfortoni et al., 2011), E-mail (Mohanmad et al., 2011), YouTube (Filippova, 2012) and Micro-blog (Liu et al., 2013).”