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Categorization and Classification of Uber Reviews

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Advances in Computing and Intelligent Systems

Part of the book series: Algorithms for Intelligent Systems ((AIS))

Abstract

This paper presents a technique for the categorization of reviews of the brand, Uber. This paper contains a classification algorithm which takes textual data as input. This algorithm takes many reviews and concepts (say, cost, safety, etc.). This algorithm is performed on online conversations happening on social media, taking into account the considered concepts. Further, the categorized reviews are classified according to the sentiment (that is, positive and negative). This paper also performs a comparison of different algorithms—Naïve Bayes, KNN, decision tree and random forest. The results of comparison of these different models are then represented using certain identified parameters.

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Author information

Authors and Affiliations

  1. Bhagwan Parshuram Institute of Technology, Rohini, India

    Mugdha Sharma, Daksh Aggarwal & Divyasha Pahuja

Authors
  1. Mugdha Sharma
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  2. Daksh Aggarwal
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  3. Divyasha Pahuja
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Corresponding author

Correspondence to Mugdha Sharma .

Editor information

Editors and Affiliations

  1. Rajasthan Technical University, Kota, Rajasthan, India

    Harish Sharma

  2. University of Southern Denmark, Odense, Denmark

    Kannan Govindan

  3. Amity University, Jaipur, Rajasthan, India

    Ramesh C. Poonia

  4. Amity University, Jaipur, Rajasthan, India

    Sandeep Kumar

  5. University of Bahrain, Zallaq, Bahrain

    Wael M. El-Medany

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Cite this paper

Sharma, M., Aggarwal, D., Pahuja, D. (2020). Categorization and Classification of Uber Reviews. In: Sharma, H., Govindan, K., Poonia, R., Kumar, S., El-Medany, W. (eds) Advances in Computing and Intelligent Systems. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-15-0222-4_31

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