TweetRush: a tool for analysis of twitter data
Автор: Avnish Dawar, Archana Purwar, Nikhil Anand, Chirag Singla
Журнал: International Journal of Education and Management Engineering @ijeme
Статья в выпуске: 2 vol.8, 2018 года.
Бесплатный доступ
Twitter network has millions of users spreading information in the form of 140 character messages called tweets. And each user expresses his or her opinion with the tweet, these tweets have been used to know a person’s state of mind, get recommendations and also predict the pattern. But a research is an effective one only if its results can be easily understood and a clear understanding requires visualization of the inferences. There isn’t any data-graph, pie chart or a tree depicting the results of twitter analysis. Hence this paper suggests “TweetRush” tool to analyze twitter data. It is able to find the influence of a particular user in his network. Graphs help us determine a user’s outreach. This tool will help advertisers to target the exact audience; budding entrepreneurs can make use of the influential factor to market their start-ups.
Twitter, internet, social media, tweet, analysis, and graph
Короткий адрес: https://sciup.org/15015759
IDR: 15015759 | DOI: 10.5815/ijeme.2018.02.04
Список литературы TweetRush: a tool for analysis of twitter data
- Ann Smarty. 5 Tools for Downloading and Analyzing Twitter Data, 2015
- Danah boyd, Scott Golder, Gilad Lotan. Tweet, Tweet, Retweet: Conversational Aspects of Retweeting on Twitter. HICSS, 2010, 412.
- Georgieva M. How to Use Hashtags on Twitter: A Simple Guide for Marketers?
- Doctor V. What Do Twitter Trends Mean?
- Zaman TR, Herbrich R, Gael VJ, Stern D. Predicting Information Spreading in Twitter.
- Devi DR,and Puduru Devi. A Probabilistic Model of Real Time Event Detection and Reporting. International Journal of Computer Science and Information Technologies 2014, 7614-7617.
- Kwak H, Lee C, Park H, and Moon S. What is Twitter, a Social Network or a News Media? Proceedings of the 19th international conference on World Wide Web 2010; 5(6): 591-600.
- Rakesh V, Reddy CK, Singh D, Ramachandran MS. Location-Specific Tweet Detection and Topic Summarization in Twitter. IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2013.
- Bolla RA. Crime pattern detection using online social media. Student Research & Creative Works, Scholar’s Mine 2014.
- Rani M, Arora J. A Review of Data Analysis of Twitter. International Journal of Advanced Research in Computer Science and Software Engineering 2016; 6:5.
- Akhilesh Kumar Singh, Deepak Kumar Gupta, Raj Mohan Singh. Sentiment Analysis of Twitter User Data on Punjab Legislative Assembly Election. I J. Modern Education and Computer Science 2017, vol.9(9), 60-68.
- Vinay K. Jain, Shishir Kumar. Towards Prediction of Election Outcome Using Social Media. I J. Modern Education and Computer Science 2017, 12, 20-28.
- Mehmood, A., Palli, A. S., & Khan, M. N. A. A study of sentiment and trend analysis techniques for social media content. International Journal of Modern Education and Computer Science, 2014, 6(12), 47.
- Deebha Mumtaz, Bindiya Ahuja. A Lexical Approach for Opinion Mining in Twitter. I J. Modern Education and Computer Science 2016, vol.6(4), 20-29.
- Jeff Zabin and Alex Jefferies. Social media monitoring and analysis: Generating consumer insights from the online conversation. Aberdeen Group Benchmark Report, January 2008.
- Asad Mehmood, Abdul S., Palli, M.N.A. Khan. A Study of Sentiment and Trend Analysis Techniques for Social Media Content. I J. Modern Education and Computer Science 2014, vol.6(12), 47-54.
