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What Multimedia Sentiment Analysis Says About City Liveability

  • Joost Boonzajer FlaesEmail author
  • Stevan RudinacEmail author
  • Marcel WorringEmail author
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9626)

Abstract

Recent developments allow for sentiment analysis on multimodal social media content. In this paper we analyse content posted on microblogging and content-sharing platforms to estimate sentiment of the city’s neighbourhoods. The results of sentiment analysis are evaluated through investigation into the existence of relationships with the indicators of city liveability, collected by the local government. Additionally, we create a set of sentiment maps that may help discover existence of possible sentiment patterns within the city. This study shows several important findings. First, utilizing multimedia data, i.e., both visual and text content leads to more reliable sentiment scores. The microblogging platform Twitter further appears more suitable for sentiment analysis than the content-sharing website Flickr. However, in case of both platforms, the computed multimodal sentiment scores show significant relationships with the indicators of city liveability.

Keywords

Multimodal sentiment analysis Semantic concept detection Social multimedia City liveability 

References

  1. 1.
    Bird, S.: Nltk: the natural language toolkit. In: Proceedings of the COLING/ACL on Interactive Presentation Sessions, pp. 69–72. Association for Computational Linguistics (2006)Google Scholar
  2. 2.
    Borth, D., Ji, R., Chen, T., Breuel, T., Chang, S.-F.: Large-scale visual sentiment ontology and detectors using adjective noun pairs. In: Proceedings of the 21st ACM International Conference on Multimedia, pp. 223–232. ACM (2013)Google Scholar
  3. 3.
    De Smedt, T., Daelemans, W.: Pattern for python. J. Mach. Learn. Res. 13, 2063–2067 (2012)zbMATHGoogle Scholar
  4. 4.
    Dignum, K., Jansen, J., Sloot, J.: Growth and decline - demography as a driving force. PLAN Amsterdam 17(5), 25–27 (2011)Google Scholar
  5. 5.
    C.G.A.O. for Research and Statistics. Fact sheet leefbaarheidsindex periode 2010–2013, Febraury 2014. https://www.amsterdam.nl/publish/pages/502037/fact_sheet_6_leefbaarheidsindex_2010_-_2013_opgemaakt_def.pdf
  6. 6.
    Mitchell, L., Frank, M.R., Harris, K.D., Dodds, P.S., Danforth, C.M.: The geography of happiness: connecting twitter sentiment and expression, demographics, and objective characteristics of place. PLoS ONE 8(5), e64417 (2013)CrossRefGoogle Scholar
  7. 7.
    Zheng, Y., Capra, L., Wolfson, O., Yang, H.: Urban computing: concepts, methodologies, and applications. ACM Trans. Intell. Syst. Technol. (TIST) 5(3), 38 (2014)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Twitter Inc.LondonUK
  2. 2.Informatics InstituteUniversity of AmsterdamAmsterdamThe Netherlands

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