Twitter topic Analysis using Multi-Tweet Sequential Summarization for Sentimental Data
Abstract & Details
Research Area
Text Mining
Keywords
Streaming data abstraction
Emoticon based opion is analyzed
Non –text feature extraction.
Abstract
The rise of social media has generated tremendous interest and changes among Internet users today. Data from these social media sites can be used for a number of purposes, like prediction, marketing or sentimental analysis. Twitter is a social networking service on which users post and interact with a message called "TWEETS". The millions of tweets received every year could be subjected to sentiment analysis. But handling such a huge amount of unstructured data is a tedious task to take up. The current Analytics tools and models used that are available in the market, but are not sufficient to manage big data. Therefore, we have utilized Hadoop for intelligent analysis and storage of big data. In this proposed work, we did sentiment analysis on tweets in Hadoop environment.
License
This work is licensed under a Creative
Commons
Attribution-ShareAlike 4.0 International License.
Author Information
| # | Name | Institute / Affiliation |
|---|---|---|
| 1 | M Dhuarshine | Anand Institute of Higher Technology |
| 2 | K Archana | Anand Institute of Higher Technology |
| 3 | D Anand Joseph Daniel | Anand Institute of Higher Technology |
How to Cite
Use the following formats to cite this article in your research.
APA Style
Dhuarshine, M, Archana, K, & Daniel, D Anand Joseph (2020). Twitter topic Analysis using Multi-Tweet Sequential Summarization for Sentimental Data. International Journal of Advance Research and Innovative Ideas In Education, 6(2), 617-623.
MLA Style
Dhuarshine, M, et al. "Twitter topic Analysis using Multi-Tweet Sequential Summarization for Sentimental Data." International Journal of Advance Research and Innovative Ideas In Education, vol. 6, no. 2, 2020, pp. 617-623.
IEEE Style
M Dhuarshine, K Archana, and D Anand Joseph Daniel, "Twitter topic Analysis using Multi-Tweet Sequential Summarization for Sentimental Data," International Journal of Advance Research and Innovative Ideas In Education, vol. 6, no. 2, pp. 617-623, 2020.
Vancouver Style
Dhuarshine M, Archana K, Daniel D Anand Joseph. Twitter topic Analysis using Multi-Tweet Sequential Summarization for Sentimental Data. International Journal of Advance Research and Innovative Ideas In Education. 2020;6(2):617-623.
Harvard Style
Dhuarshine, M, Archana, K, & Daniel, D Anand Joseph (2020) 'Twitter topic Analysis using Multi-Tweet Sequential Summarization for Sentimental Data', International Journal of Advance Research and Innovative Ideas In Education, 6(2), pp. 617-623.
Chicago Style
Dhuarshine, M, K Archana, and D Anand Joseph Daniel. "Twitter topic Analysis using Multi-Tweet Sequential Summarization for Sentimental Data." International Journal of Advance Research and Innovative Ideas In Education 6, no. 2 (2020): 617-623.
Turabian Style
Dhuarshine, M, K Archana, and D Anand Joseph Daniel. "Twitter topic Analysis using Multi-Tweet Sequential Summarization for Sentimental Data." International Journal of Advance Research and Innovative Ideas In Education 6, no. 2 (2020): 617-623.
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