Abstract
Understanding customers’ opinion and subjectivity is regarded as an important task in various domains (e.g., marketing). Particularly, with many types of social media (e.g., Twitter and FaceBook), such opinions are propagated to other users and might make a significant influence on them. In this paper, we propose a method for understanding relationship between sentiment content corresponding with its diffusion degree in Online Social Networks. Thereby, a practical system, called TweetScope, has been implemented to efficiently collect and analyze all possible tweets from customers.
The original version of this chapter was revised: The copyright line was incorrect. This has been corrected. The Erratum to this chapter is available at DOI: 10.1007/978-3-319-05939-6_37
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- 1.
Natural Language Toolkit package can be downloaded at http://nltk.org.
- 2.
http://twitaholic.com - \(Twitterholics\) is an online service that scan Twitter a few times a day to determine who is the biggest account.
- 3.
https://dev.twitter.com/docs provides a detail description about the latest version 1.1 of Twitter API.
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Acknowledgement
This work was supported by the BK21+ Program of the National Research Foundation (NRF) of Korea.
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© 2014 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering
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Trung, D.N., Nguyen, T.T., Jung, J.J., Choi, D. (2014). Understanding Effect of Sentiment Content Toward Information Diffusion Pattern in Online Social Networks: A Case Study on TweetScope. In: Vinh, P., Alagar, V., Vassev, E., Khare, A. (eds) Context-Aware Systems and Applications. ICCASA 2013. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 128. Springer, Cham. https://doi.org/10.1007/978-3-319-05939-6_34
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