User sentiment detection: a YouTube use case

Choudhury, Smitashree and Breslin, John G. (2010). User sentiment detection: a YouTube use case. In: The 21st National Conference on Artificial Intelligence and Cognitive Science, 30 Aug - 1 Sep 2010, Galway, Ireland.

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Abstract

In this paper we propose an unsupervised lexicon-based approach to detect the sentiment polarity of user comments in YouTube. Polarity detection in social media content is challenging not only because of the existing limitations in current sentiment dictionaries but also due to the informal linguistic styles used by users. Present dictionaries fail to capture the sentiments of community-created terms. To address the challenge we adopted a data-driven approach and prepared a social media specific list of terms and phrases expressing user sentiments and opinions. Experimental evaluation shows the combinatorial approach has greater potential. Finally, we discuss many research challenges involving social media sentiment analysis.

Item Type:

Conference or Workshop Item

The Authors

Project Funding Details:

Funded Project Name	Project ID	Funding Body
Not Set	Not Set	Science Foundation Ireland under grant number SFI/08/CE/I1380 (Líon 2)

Academic Unit/School:

Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)

Item ID:

32459

Depositing User:

Smitashree Choudhury

Date Deposited:

07 Feb 2012 17:27

Last Modified:

07 Dec 2018 12:04

URI:

http://oro.open.ac.uk/id/eprint/32459

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