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Users’ Topic Detection from Tweets based on Keyword Extraction

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
G. Hemantha Kumar, Seyedmahmoud Talebi, Manoj K.

Hemantha G Kumar, Seyedmahmoud Talebi and Manoj K.. Users’ Topic Detection from Tweets based on Keyword Extraction. International Journal of Computer Applications 167(9):32-35, June 2017. BibTeX

	author = {G. Hemantha Kumar and Seyedmahmoud Talebi and Manoj K.},
	title = {Users’ Topic Detection from Tweets based on Keyword Extraction},
	journal = {International Journal of Computer Applications},
	issue_date = {June 2017},
	volume = {167},
	number = {9},
	month = {Jun},
	year = {2017},
	issn = {0975-8887},
	pages = {32-35},
	numpages = {4},
	url = {},
	doi = {10.5120/ijca2017914382},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


In this paper, a different approach for detecting users’ topic of interest in twitter based on keyword extraction methods and neural network has been shown. An approach to Text Mining is proposed by extracting the topics relevant to some keywords and further used in predicting topics from users’ tweets (Twitter posts). The TF-IDF method has been used to extract keywords in this work. The proposed method, which uses neural network, has been shown to be efficient for topic detection and further comparison. Back propagation method is used to train and to learn the neural network.


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Neural Network, Keyword Extraction, Topic Detection, Twitter.