Analysing for Impact of Neutral Sentiments for Enhancing Quality of Services

Sentiment analysis (SA) is an intellectual process of extracting a user's views. Social media is gaining prominence in public transit agencies for communication strategies and daily management. In recent years, web documents are identified as an important source of reviewing individual opinions. Researchers using these social networking platforms are producing a high rate of increase in interest in methods for automatically extracting and analysing opinions from web documents such as for weblogs, customer reviews, movies and public services etc. This paper is an attempt to perform an evaluation of public opinion for the Quality of Services of two very popular public transportations in North India. Opinions of public have been collected in form of tweets for a specific time. An approach based on fuzzy logic and machine learning is introduced to solve the tweets extraction that is used for classification. The impact of neutral tweets is discussed. Results show that the performance of road transport is better than the transport through railway services and neutral tweets play a significant role in emotion analysis of the system.