Tweet the debates: understanding community annotation of uncollected sources

By David A. Shamma, L. Kennedy, Elizabeth F. Churchill. WSM@MM, 2009

389 citations recorded by the source corpus.

Subfields: Communication, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/3e8f99514a816cfc0a6149c0c6c69b65aa4c7761

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Citations in the corpus

Exploiting social relations for sentiment analysis in microblogging (2013, background): “This dataset consists of 3,269 tweets posted during the presidential debate on September 26, 2008 between Barack Obama and John McCain [34].”
Twitter Polarity Classification with Label Propagation over Lexical Links and the Follower Graph (2011, methodology): “Evaluation is performed on several datasets of tweets that have been annotated for polarity: the Stanford Twitter Sentiment set (Go et al., 2009), tweets from the 2008 debate between Obama and McCain (Shamma et al., 2009), and a new dataset of tweets about health care reform that we have created.”
Unsupervised sentiment analysis with emotional signals (2013, background): “The second data set is Obama-McCain Debate (OMD).5 This dataset consists of 3,269 tweets posted during the presidential debate on September 26, 2008 between Barack Obama and John McCain [29].”
Like It or Not (2016, methodology): “Two different datasets were used for the evaluation of the ESSA approach, the STS [Go et al. 2009] and the OMD [Shamma et al. 2009] datasets.”
Discovering users' topics of interest on twitter: a first look (2010, background): “We then develop a topic pro.le, which characterizes users topics of interest, by discerning which categories appear frequently and cover the entities.”
Semantic Sentiment Analysis of Twitter (2012, neutral): “presidential TV debate in September 2008 [13].”
On Using Twitter to Monitor Political Sentiment and Predict Election Results (2011, background): “Previously Shamma et al. examined a variety of aspects of debate modelling using Twitter, beyond individual politician performance (Shamma et al., 2009).”
Evaluation Datasets for Twitter Sentiment Analysis: A survey and a new dataset, the STS-Gold (2013, background): “presidential TV debate in September 2008 [22].”
On Stopwords, Filtering and Data Sparsity for Sentiment Analysis of Twitter (2014, methodology): “• The Obama-McCain Debate dataset (OMD) (Shamma et al., 2009).”