Author(s):
Lovedeep Singh
Kanishk Gautam
An attempt on Twitter ‘likes’ grading strategy using pure linguistic feature engineering: A novel approach*
Abstract. Twitter is one of the most popular social platform used for sharing thoughts about different aspects may it be emotional like ‘love’, ‘motivation’, ‘dedication’, etc. businesses like ‘marketing’, ‘startup’, ‘blogging’, etc. or health like ‘gym’, ‘fitness’, ‘food’, etc., and similar areas. People follow hashtags for topics in their interest. Agreement of a tweet can be measured by likes or retweets. This paper deals with pure linguistic features other than using embeddings in vector space via TFIDF or Doc2Vec. This paper deals with a collection of tweets on such hashtags and classifying the level of likes the tweet will get using pure linguistic features in the form of a grade.
Proceedings published in LNEE-Springer
Accepted at MDCWC2020 ( Springer ) - Workshop on Machine learning, Deep learning and Computational Intelligence for Wireless Communication
