Technology Trend Analysis Tool using Twitter as a Source

Authors

  • Yi-Chun Lin National Taiwan University
  • Ping-che Yang
  • Wen-Tai Hsieh
  • Seng-cho T. Chou

Keywords:

Trend analysis, content based recommendation, News recommendation, social recommendation, Twitter, Social media

Abstract

As the rise of social networking, people started to share information through different kinds of social media. Among all varieties of social media, Twitter is a valuable resource for data mining because of its prevalence and recognition by celebrities. In this paper we present a novel system which collects Tweets from technology celebrities, by using data mining technique, we’ll be able to do trend analysis on those Tweets and thus provide some prediction of future trend. Results of trend analysis will be display as a website with different sections presenting top news, trend topics, active users, and top sources.

Author Biographies

Yi-Chun Lin, National Taiwan University

Department of Information Management
National Taiwan University
Taipei, Taiwan

Ping-che Yang

Institute for Information Industry
Taipei, Taiwan

Wen-Tai Hsieh

Department of Information Management
National Taiwan University
Taipei, Taiwan

Seng-cho T. Chou

Department of Information Management
National Taiwan University
Taipei, Taiwan

References

S. Wasserman and K. Faust, Social network analysis : methods and applications. Cambridge; New York: Cambridge University Press, 1994.

J. A. Barnes, "Class and Committees in a Norwegian Island Parish," Human Relations, vol. 7, pp. 39-58, 1954.

S. Milstein, A. Chowdhury, G. Hochmuth, B. Lorica, and R. Magoulas. (2008). Twitter and the micromessaging revolution: Communication,connections, and immediacy.140 characters at a time.

A. Cheng, M. Evans, and N. Koudas. (2009, July 13). Inside the Political Twittersphere. Available: http://www.sysomos.com/insidetwitter/politics/

A. Yong-Yeol, H. Seungyeop, K. Haewoon, M. Sue, and J. Hawoong, "Analysis of topological

characteristics of huge online social networking services," in Proceedings of the 16th international conference on World Wide Web, ed. Banff, Alberta, Canada: ACM, 2007, pp. 835-844.

e. Articles. (2012, July 13). Top 15 Most Popular Social Networking Sites | July 2012. Available: http://www.ebizmba.com/articles/social-networking-websites

B. D. Longueville, R. S. Smith, and G. Luraschi, ""OMG, from here, I can see the flames!": a use case of mining location based social networks to acquire spatio-temporal data on forest fires," presented at the Proceedings of the 2009 International Workshop on Location Based Social Networks, Seattle, Washington, 2009.

T. Sakaki, M. Okazaki, and Y. Matsuo, "Earthquake shakes Twitter users: real-time event detection by social sensors.," M. Rappa, P. Jones, J. Freire, and S. Chakrabarti, Eds., ed: ACM, 2010, pp. 851-860.

A. Pak and P. Paroubek, "Twitter as a Corpus for Sentiment Analysis and Opinion Mining " in Proceedings of the Seventh conference on International Language Resources and Evaluation (LREC'10), ed. Valletta, Malta: European Language Resources Association (ELRA), 2010.

O. Phelan, K. McCarthy, and B. Smyth, "Using twitter to recommend real-time topical news," presented at the Proceedings of the third ACM conference on Recommender systems, New York, New York, USA, 2009.

M. Michael and K. Nick, "TwitterMonitor: trend detection over the twitter stream," in Proceedings of the 2010 ACM SIGMOD International Conference on Management of data, ed. Indianapolis, Indiana, USA: ACM, 2010, pp. 1155-1158.

Published

2012-12-15

How to Cite

Lin, Y.-C., Yang, P.- che ., Hsieh, W.-T. ., & T. Chou, S.- cho . (2012). Technology Trend Analysis Tool using Twitter as a Source. International Journal on Information Technology and Computer Science, 6(1). Retrieved from http://ijitcs.info/index.php/ijitcs/article/view/56

Issue

Section

Research Articles