Abstract
Due to the recent popularization of smartphones, it has become easy to get connected on Social Network Service (SNS) which caused the proliferation on the amount of tweets on Twitter. Many studies have been proposed to discover valuable meanings from Twitter text messages by using opinion mining. However, these researches have a side effect that it is only focused on positive and negative in the limited category. In this paper, we will attempt to examine which factors could affect the users interests or preferences by analyzing and comparing smartphone product reviews which were posted on Twitter, in multilateral categories, by using opinion mining.
Keywords
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Marketresearch on digital media, internet marketing, http://www.emarketer.com
Kang, J., Kim, C., Yoo, S., Lee, Y., Park, H., Kim, Y.: Recommendation of Acquaintances to Follow in Twitter. In: The 38th Domestic Conference on Korean Institute of Information Scientists and Engineers, Korea, vol. 38(2), pp. 383–386 (2011)
Lee, G., Lee, E., Kwak, K., Park, J., Je, R., Kim, J.: A study on charactheristics of Twitter users (compared to Cyworld, Facebook). In: HCI 2011, pp. 1043–1050 (2011)
Kim, J., Ko, B., Jeong, H., Kim, P.: A Method for Extracting Topics in News Twitter. 7th International Journal of Software Engineering and Its Applications 7(2), 1–6 (2013)
Lee, J., Kim, C.: Analysis of the Information Diffusion Process on Twitter:Effects of Influentials and Hyperlinks. Korean Journal of Journalism & Communication Studies 56(3), 238–265 (2012)
Hwang, M., Choi, D., Kim, P.: A Context Information Extraction Method according to Subject for Semantic Text Processing. Journal of Korean Institute of Information Technology 8(11), 197–204 (2010)
Hwang, M., Kim, P.: An Enrichment Method on Semantic Relation Network of WordNet. Journal of Korean Institute of Information Technology 7(5), 209–215 (2009)
Park, K., Hwang, K.: A Bio-Text Mining System Based on Natural Language Processing. Journal of KISS: Computing Practices 17(4), 205–213 (2011)
Choi, Y., Park, S.: Interplay of Text Mining and Data Mining for Classifying Web Contents. Korean Journal of Cognitive Science 13(3), 33–46 (2002)
Pang, B., Lee, L.: Opinion Mining and Sentiment Analysis. Foundations and Trends in Information Retrieval 2(1-2), 1–135 (2008)
Yang, J., Myung, J., Lee, S.: A Sentiment Classification Method Using Context Information in Product Review Summarization. Journal of KISS: Database 36(4), 254–262 (2009)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Kim, J., Choi, D., Hwang, M., Kim, P. (2014). Analysis on Smartphone Related Twitter Reviews by Using Opinion Mining Techniques. In: Sobecki, J., Boonjing, V., Chittayasothorn, S. (eds) Advanced Approaches to Intelligent Information and Database Systems. Studies in Computational Intelligence, vol 551. Springer, Cham. https://doi.org/10.1007/978-3-319-05503-9_20
Download citation
DOI: https://doi.org/10.1007/978-3-319-05503-9_20
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-05502-2
Online ISBN: 978-3-319-05503-9
eBook Packages: EngineeringEngineering (R0)