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Topic Modelling for Research Perception: Techniques, Processes and a Case Study

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Recent Innovations in Artificial Intelligence and Smart Applications

Part of the book series: Studies in Computational Intelligence ((SCI,volume 1061))

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Abstract

There is a need for an automated approach to extract current trends and perceptions from literature review material in a field of interest. Manually reviewing a large number of papers is time-consuming, topic modelling will help to avoid this. The text mining technique chosen for this task is topic modelling. The chapter gives an overview of the most widely used topic modelling techniques, as well as a few applications. It also summarizes a few current research trends and the generic processes of topic modelling. A section demonstrates an approach to discovering current perceptions from literature materials focused on data analytics in e-commerce using topic modelling. The case study framework included five steps: data collection, data pre-processing, topic tuning, performance evaluation, and interpretation of topic modelling results. The topic numbers were tuned using MALLET with Gensim wrappers. LDA is used. The Gensim topic coherence framework in Python was used to evaluate the topics. The perceptions in the reviewed material are interpreted using the inter-topic distance map in pyLDAVis. The modelling revealed distinct perceptions or directions of interest in e-commerce and data analytics research. Researchers can use topic modelling to see which areas are getting attention and which aren’t.

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Authors and Affiliations

  1. Department of Computer and Information Sciences, Covenant University, Ota, Nigeria

    Ibukun T. Afolabi & Christabel N. Uzor

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  1. Ibukun T. Afolabi
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  2. Christabel N. Uzor
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Correspondence to Christabel N. Uzor .

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Editors and Affiliations

  1. Faculty of Engineering & IT, The British University in Dubai, Dubai, United Arab Emirates

    Mostafa Al-Emran

  2. Faculty of Engineering & IT, The British University in Dubai, Dubai, United Arab Emirates

    Khaled Shaalan

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Afolabi, I.T., Uzor, C.N. (2022). Topic Modelling for Research Perception: Techniques, Processes and a Case Study. In: Al-Emran, M., Shaalan, K. (eds) Recent Innovations in Artificial Intelligence and Smart Applications. Studies in Computational Intelligence, vol 1061. Springer, Cham. https://doi.org/10.1007/978-3-031-14748-7_13

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