Real Time Opinion Mining and Analysis of Twitter Data

  • Authors

    • K Senthil Kumar
    • Mohammad Musab Trumboo
    • Vaibhav .
    • Satyajai Ahlawat
    2018-07-20
    https://doi.org/10.14419/ijet.v7i3.12.16104
  • Sentimental Analysis, TextBlob, Naive Bayes Classifier, NLP, Tweepy, Twitter API.

  • Abstract

    This era, in which we currently stand, is an era of public opinion and mass information. People from all around the globe are joined together through various information junctions to create a global community, where one thing from the far east reaches to the people of the far west within seconds. Nothing is hidden, everything and anything can be scrutinized to its core and through these global criticisms and mass discussions of gigantic magnitude, we have reached to the pinnacle of correct decisions and better choices. These pseudo social groups and data junctions have bombarded our society so much that they now hold the forelock of our opinions and sentiments, ergo, we reach out to these groups to achieve a better outcome. But, all this enormous data and all these opinions cannot be researched by a single person, hence, comes the need of sentiment analysis. In this paper we’ll try to accomplish this by creating a system that will enable us to fetch tweets from twitter and use those tweets against a lexical database which will create a training set and then compare it with the pre-fetched tweets. Through this we will be able to assign a polarity to all the tweets by means of which we can address them as negative, positive or neutral and this is the very foundation of sentiment analysis, so subtle yet so magnificent.

     

     

  • References

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  • How to Cite

    Senthil Kumar, K., Musab Trumboo, M., ., V., & Ahlawat, S. (2018). Real Time Opinion Mining and Analysis of Twitter Data. International Journal of Engineering & Technology, 7(3.12), 351-353. https://doi.org/10.14419/ijet.v7i3.12.16104

    Received date: 2018-07-23

    Accepted date: 2018-07-23

    Published date: 2018-07-20