Encyclopedia of Social Network Analysis and Mining

2018 Edition
| Editors: Reda Alhajj, Jon Rokne

Sentiment Analysis in Social Media

  • Noor Fazilla Abd Yusof
  • Chenghua Lin
  • Yulan He
Reference work entry
DOI: https://doi.org/10.1007/978-1-4939-7131-2_120

Synonyms

Glossary

NB

Naive Bayes classifier

SVM

Support vector machines

MaxEnt

Maximum entropy classifier

PMI

Point-wise mutual information

POS

Part-of-speech

SO

Sentiment orientation

Definition

Sentiment analysis aims to understand subjective information such as opinions, attitudes, and feelings expressed in text. Sentiment analysis tasks include but not limited to the following:
  • Sentiment classification which classifies a given piece of text as positive, negative, or neutral.

  • Opinion retrieval which retrieves opinions in relevance to a specific topic or query.

  • Opinion summarization which summarizes opinions over multiple text sources towards a certain topic.

  • Opinion holder identification which identifies who express a specific opinion.

  • Topic/sentiment dynamics tracking which aims to track sentiment and topic changes over time.

  • Opinion spam detectionwhich identifies fake/untruthful...

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Notes

Acknowledgments

This work is supported by the awards made by the UK Engineering and Physical Sciences Research Council (Grant number: EP/P005810/1) and the UK Economic & Social Research Council (Grant number: ES/P011004/1).

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Copyright information

© Springer Science+Business Media LLC, part of Springer Nature 2018

Authors and Affiliations

  • Noor Fazilla Abd Yusof
    • 1
  • Chenghua Lin
    • 1
  • Yulan He
    • 2
  1. 1.Department of Computing ScienceUniversity of AberdeenAberdeenUK
  2. 2.School of Engineering and Applied Science, Aston UniversityBirminghamUK

Section editors and affiliations

  • Thomas Gottron
    • 1
  • Stefan Schlobach
    • 2
  • Steffen Staab
    • 3
  1. 1.Institute for Web Science and TechnologiesUniversität Koblenz-LandauKoblenzGermany
  2. 2.YUAmsterdamThe Netherlands
  3. 3.Institute for Web Science and TechnologiesUniversität Koblenz-LandauKoblenzGermany