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Improvisation of Cleaning Process on Tweets for Opinion Mining

Improvisation of Cleaning Process on Tweets for Opinion Mining

Arpita Grover, Pardeep Kumar, Kanwal Garg
Copyright: © 2020 |Volume: 5 |Issue: 1 |Pages: 11
ISSN: 2379-738X|EISSN: 2379-7371|EISBN13: 9781799808374|DOI: 10.4018/IJBDAH.2020010104
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MLA

Grover, Arpita, et al. "Improvisation of Cleaning Process on Tweets for Opinion Mining." IJBDAH vol.5, no.1 2020: pp.49-59. http://doi.org/10.4018/IJBDAH.2020010104

APA

Grover, A., Kumar, P., & Garg, K. (2020). Improvisation of Cleaning Process on Tweets for Opinion Mining. International Journal of Big Data and Analytics in Healthcare (IJBDAH), 5(1), 49-59. http://doi.org/10.4018/IJBDAH.2020010104

Chicago

Grover, Arpita, Pardeep Kumar, and Kanwal Garg. "Improvisation of Cleaning Process on Tweets for Opinion Mining," International Journal of Big Data and Analytics in Healthcare (IJBDAH) 5, no.1: 49-59. http://doi.org/10.4018/IJBDAH.2020010104

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Abstract

In the current scenario, high accessibility to computational facilities encourage generation of a large volume of electronic data. Expansion of the data has persuaded researchers towards critical analyzation so as to extract the maximum possible patterns for wiser decisiveness. Such analysis requires curtailing of text to a better structured format by pre-processing. This scrutiny focuses on implementing pre-processing in two major steps for textual data generated by dint of Twitter API. A NoSQL, document-based database named as MongoDB is used for accumulating raw data. Thereafter, cleaning followed by data transformation is executed on accumulated tweets related to Narender Modi, Honorable Prime Minister of India.