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Twitter Microblog Sentiment Analysis

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Encyclopedia of Social Network Analysis and Mining

Synonyms

Microblog sentiment analysis; Twitter opinion mining

Glossary

Sentiment Analysis:

The automatic analysis of opinions, sentiments, and subjectivity in text. It aims to determine the sentiment associated with a topic or context

Online Learning:

Online learning algorithms update the learning model incrementally whenever they receive new data. They are usually highly efficient and scalable

Multitask Learning:

The problem of jointly solving several related machine learning tasks by leveraging the commonality among tasks

Definition

Twitter microblog sentiment analysis aims to identify and detect the sentiments or emotions present in a microblog post. The techniques developed for microblog sentiment analysis can also be applied to classify social media data in a real-time manner.

Introduction

Microblogs, such as Twitter (http://www.twitter.com) and Facebook status updates (http://www.facebook.com), allow users to publish short snippets of text online. Compared to blogs, microblogs...

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References

  • Barbosapp L, Feng J (2010) Robust sentiment detection on Twitter from biased and noisy data. In: COLING (posters), Beijing, pp 36–44

    Google Scholar 

  • Bifet A, Frank E (2010) Sentiment knowledge discovery in Twitter streaming data. In: Pfahringer B, Holmes G, Hoiffmann A (eds) Discovery science. Springer, Berlin, pp 1–15

    Google Scholar 

  • Crammer K, Dekel O, Keshet J, Shalev-Shwartz S, Singer Y (2006) Online passive-aggressive algorithms. J Mach Learn Res 7:551–585

    MATH  MathSciNet  Google Scholar 

  • Davidov D, Tsur O, Rappoport A (2010a) Enhanced sentiment learning using Twitter hashtags and smileys. In: COLING (posters), Beijing, pp 241–249

    Google Scholar 

  • Davidov D, Tsur O, Rappoport A (2010b) Semi-supervised recognition of sarcastic sentences in Twitter and amazon. In: Proceeding of the 23rd international conference on computational linguistics (COLING), Beijing

    Google Scholar 

  • Java A, Song X, Finin T, Tseng BL (2007) Why we Twitter: an analysis of a microblogging community. In: WebKDD/SNA-KDD, San Jose, pp 118–138

    Google Scholar 

  • Kouloumpis E, Wilson T, Moore J (2011) Twitter sentiment analysis: the good the bad and the omg! In: ICWSM, Barcelona

    Google Scholar 

  • Li G, Hoi SCH, Chang K, Jain R (2010) Micro-blogging sentiment detection by collaborative online learning. In: ICDM, Sydney, pp 893–898

    Google Scholar 

  • Li G, Chang K, Hoi SCH, Liu W, Jain R (2011) Collaborative online learning of user generated content. In: CIKM, Glasgow, pp 285–290

    Google Scholar 

  • Pak A, Paroubek P (2010) Twitter as a corpus for sentiment analysis and opinion mining. In: LREC, Valletta

    Google Scholar 

  • Pang B, Lee L (2007) Opinion mining and sentiment analysis. Found Trends Inf Retr 2(1–2):1–135

    Google Scholar 

  • Pang B, Lee L, Vaithyanathan S (2002) Thumbs up? Sentiment classification using machine learning techniques. In Proceedings of EMNLP, Stroudsburg, pp 79–86

    Google Scholar 

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Li, G., Chang, K., Hoi, S.C.H. (2014). Twitter Microblog Sentiment Analysis. In: Alhajj, R., Rokne, J. (eds) Encyclopedia of Social Network Analysis and Mining. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6170-8_265

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