TWITTER SENTIMENT ANALYSIS

Main Article Content

Rakesh Ranjan Rahul Bind Rishabh Sahu Anurag .

Abstract

Abstract: Since an ever-increasing part of the population makes use of social media in their day-to-day lives, social media data is being analyzed in many different disciplines. The social media analytics process involves four distinct steps, data discovery, collection, preparation, and analysis. While there is a great deal of literature on the challenges and difficulties involving specific data analysis methods, there hardly exists research on the stages of data discovery, collection, and preparation. To address this gap, we conducted an extended and structured literature analysis through which we identified challenges addressed and solutions proposed. The literature search revealed that the volume of data was most often cited as a challenge by researchers. In contrast, other categories have received less attention. Based on the results of the literature search, we discuss the most important challenges for researchers and present potential solutions. The findings are used to extend an existing framework on social media analytics. The article provides benefits for researchers and practitioners who wish to collect and analyze social media data.[1]


Index Terms: Social media Scraping Behavior economics Sentiment analysis Opinion mining NLP Toolkits Software platforms

Article Details

How to Cite
Ranjan, R., Bind, R., Sahu, R., & ., A. (2020). TWITTER SENTIMENT ANALYSIS. International Journal of Engineering Technology and Computer Research, 8(4). Retrieved from http://ijetcr.org/index.php/ijetcr/article/view/518
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