Topic sentiment analysis in twitter: a graph-based hashtag sentiment classification approach

By Xiaolong Wang, Furu Wei, Xiaohua Liu, M. Zhou, Ming Zhang. International Conference on Information and Knowledge Management, 2011

481 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/1199b8d6ecb5669cf24144a7364fcec01f32e137

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In Artificial Intelligence

In Statistical and Nonlinear Physics

Citations in the corpus

Machine Vision and Social Media Images: Why Hashtags Matter (2020, methodology): “After locating the most frequently appearing hashtags in the co-occurrence network, a manual coding scheme (adapted from X. Wang et al., 2011) was used to group hashtags.”
Large Scale Sentiment Analysis on Twitter with Spark (2016, methodology): “Distribution of this paper is permitted under the terms of the Creative Commons license CCby-nc-nd 4.0”
Exploiting Social Relations and Sentiment for Stock Prediction (2014, methodology): “Various extensions of the traditional LDA model (Blei et al., 2003) has been proposed for modeling social media data (Wang et al., 2011, Jo and Oh, 2011; Liu et al., 2007; Mei et al., 2007; Diao et al., 2012).”
Bots increase exposure to negative and inflammatory content in online social systems (2018, unknown): “This network definition is in agreement with previous large-scale studies (37).”
Gated Neural Networks for Targeted Sentiment Analysis (2016, background): “…sentiment analysis (Hu and Liu 2004; Popescu and Etzioni 2007), which extracts product features and opinions towards them from user reviews, and topic-oriented sentiment analysis (Yi et al. 2003; Wang et al. 2011), which extracts features and/or sentiments towards certain topics or subjects.”
Like It or Not (2016, methodology): “Instead of using emotion tokens, Wang et al. [2011] proposed a graph-based model that leveraged co-occurrence of hashtags to classify the sentiment of certain hashtags.”
Exploring Demographic Language Variations to Improve Multilingual Sentiment Analysis in Social Media (2013, background): “There has also been a considerable amount of work in subjectivity and sentiment analysis over the past decade, including, more recently, in microblogs (Barbosa and Feng, 2010; Bermingham and Smeaton, 2010; Pak and Paroubek, 2010; Bifet and Frank, 2010; Davidov et al., 2010; Li et al., 2010; Kouloump”