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International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction and Behavior Representation in Modeling and Simulation

SBP-BRiMS 2016: Social, Cultural, and Behavioral Modeling pp 291–300Cite as

Contextual Sentiment Analysis

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9708))

Abstract

This study examines the role of context in evaluating responses to social media posts online. Current sentiment analysis tools evaluate the content of posts without considering the broader context that the post comes from. Utilizing data from an in-person study, we examine differences between perceived sentiment evaluation when social media response posts are viewed in isolation and perceived sentiment evaluation when social media responses are viewed in the context of the original post. We find that evaluations of responses viewed in context change over 50 % of the time. We validate this finding by utilizing simulated data to show the result is not simply a result of data manipulation or noisy data; furthermore, we explore results of this finding with current sentiment analysis tools, examining this result with subsets of our data with high and low kappa values.

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References

  1. Pang, B., Lee, L.: Opinion Mining and Sentiment Analysis. FNT Inf. Retrieval 2(1), 1–135 (2008)

    Article  Google Scholar 

  2. Grimmer, J., Stewart, B.M.: Text as data: the promise and pitfalls of automatic content analysis methods for political texts. Polit. Anal. 21(3), 267–297 (2013)

    Article  Google Scholar 

  3. Thelwall, M., Buckley, K., Paltoglou, G., Cai, D., Kappas, A.: Sentiment strength detection in short informal text. J. Am. Soc. Inf. Sci. Technol. 61(12), 2544–2558 (2010)

    Article  Google Scholar 

  4. Esuli, A., Sebastiani, F.: Sentiwordnet: a publicly available lexical resource for opinion mining. In: Presented at the Proceedings of LREC (2006)

    Google Scholar 

  5. Pennebaker, J.W., Chung, C.K., Ireland, M.: The development and psychometric properties of LIWC2007. In: LIWC.net, Austin, TX, USA, LIWC2007 (2007)

    Google Scholar 

  6. Stone, P.J.: User’s Manual for The General Inquirer. MIT Press, Cambridge (1968)

    Google Scholar 

  7. Agarwal, A., Xie, B., Vovsha, I., Rambow, O., Passonneau, R.: Sentiment analysis of twitter data. In: Proc. ACL 2011 Workshop on Languages in Social Media, pp. 30–38 (2011)

    Google Scholar 

  8. Davidov, D., Tsur, O., Rappoport, A.: Enhanced sentiment learning using twitter hashtags and smileys. In: ACL Proceedings of the 23rd International Conference on Computational Linguistics Posters, pp. 241–249 (2010)

    Google Scholar 

  9. Bermingham, A., Conway, M., McInerney, L., O’Hare, N., Smeaton, A.F.: Combining social network analysis and sentiment analysis to explore the potential for online radicalisation. In: IEEE 2009, pp. 231–236 (2009)

    Google Scholar 

  10. Thelwall, M., Buckley, K., Paltoglou, G.: Sentiment strength detection for the social web. J. Am. Soc. Inf. Sci. Technol. 63(1), 163–173 (2012)

    Article  Google Scholar 

  11. Lovin, L.S.: Affect control theory: an assessment. J. Math. Soc. 13(1), 171–192 (1987)

    Article  MathSciNet  Google Scholar 

  12. Heise, D.R.: Affect control theory: concepts and model. J. Math. Soc. 13(1), 1–33 (1987)

    Article  MathSciNet  MATH  Google Scholar 

  13. Osgood, C.E., May, W.H., Miron, M.S.: Cross-cultural Universals of Affective Meaning. University of Illinois Press, Urbana (1975)

    Google Scholar 

  14. Smith-Lovin, L., Robinson, D.T.: Interpreting and Responding to Events in Arabic Culture. Office of Naval Research, Grant N00014-09-1-0556, August 2015

    Google Scholar 

  15. Frankenstein, W., Joseph, K., Carley, K.M.: Social Media ACTion: SOLO Data Description. Technical report, CMU-ISR-16-103 (2016)

    Google Scholar 

  16. Hutto, C.J., Gilbert, E.: VADER: a parsimonious rule-based model for sentiment analysis of social media text. In: Eighth International AAAI Conference on Weblogs and Social Media (2014)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Carnegie Mellon University, Pittsburgh, PA, USA

    Will Frankenstein, Kenneth Joseph & Kathleen M. Carley

Authors
  1. Will Frankenstein
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  2. Kenneth Joseph
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  3. Kathleen M. Carley
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Corresponding author

Correspondence to Will Frankenstein .

Editor information

Editors and Affiliations

  1. University of Toledo, Toledo, Ohio, USA

    Kevin S. Xu

  2. Penn State University, University Park, Pennsylvania, USA

    David Reitter

  3. Penn State University, University Park, Pennsylvania, USA

    Dongwon Lee

  4. University of Saskatchewan, Saskatoon, Saskatchewan, Canada

    Nathaniel Osgood

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© 2016 Springer International Publishing Switzerland

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Frankenstein, W., Joseph, K., Carley, K.M. (2016). Contextual Sentiment Analysis. In: Xu, K., Reitter, D., Lee, D., Osgood, N. (eds) Social, Cultural, and Behavioral Modeling. SBP-BRiMS 2016. Lecture Notes in Computer Science(), vol 9708. Springer, Cham. https://doi.org/10.1007/978-3-319-39931-7_28

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  • DOI: https://doi.org/10.1007/978-3-319-39931-7_28

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-39930-0

  • Online ISBN: 978-3-319-39931-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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