• Mineeta Khanuja
• Leelkanth Dewangan

Sentiment Analysis (SA) or Mood Classification or Mood Classification is the mathematical modelling approach of person’s sentiments, insolences and mood toward an object. The object can signify events, individuals, or issues. Persons express sentiments as part of day-by-day communiqué. Sentiments can be umpired by a mish mash of indications such as facial emotions, prosodies, shrugs, and actions. Emotions are also enunciated by written texts or from their handwriting style. Linguistic is a prevailing tool to converse and pass on the information. Automatic sentiment classification and examination methods are useful in numerous applications with psychosomatic basis. For instance, it can be magnificently applied to acquire user favorites and comforts from users’ personal written text and vocalizations. These methods are frequently considered in the field of the domain of behavior or mood modeling and customer response analysis. In this paper we have applied logistic regression as classifier, and we have achieved 98% accuracy.

"An Efficient Approach for Sentiment Classification using Logistic Regression ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 6, page no.476-481, June-2018, Available :http://www.jetir.org/papers/JETIR1806458.pdf

"An Efficient Approach for Sentiment Classification using Logistic Regression ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 6, page no. pp476-481, June-2018, Available at : http://www.jetir.org/papers/JETIR1806458.pdf