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Topic Classification for Short Texts

In: Advances in Information Systems Development

Author

Listed:
  • Dan Claudiu Neagu

    (Cicada Technologies
    Babes-Bolyai University)

  • Andrei Bogdan Rus

    (Cicada Technologies
    Technical University)

  • Mihai Grec

    (Cicada Technologies)

  • Mihai Boroianu

    (Cicada Technologies)

  • Gheorghe Cosmin Silaghi

    (Babes-Bolyai University)

Abstract

In the context of TV and social media surveillance, constructing models to automate topic identification of short texts is a key task. This paper constructs worth-to-consider models for practical usage, employing Top-K multinomial classification methodology. We describe the full data processing pipeline, discussing about dataset selection, text preprocessing, feature extraction, model selection and learning, including hyperparameter optimization. We will test and compare popular methods including: standard machine learning, deep learning, and a fine-tuned BERT for topic classification.

Suggested Citation

  • Dan Claudiu Neagu & Andrei Bogdan Rus & Mihai Grec & Mihai Boroianu & Gheorghe Cosmin Silaghi, 2023. "Topic Classification for Short Texts," Lecture Notes in Information Systems and Organization, in: Gheorghe Cosmin Silaghi & Robert Andrei Buchmann & Virginia Niculescu & Gabriela Czibula & Chris Bar (ed.), Advances in Information Systems Development, pages 207-222, Springer.
    • Handle: RePEc:spr:lnichp:978-3-031-32418-5_12
    DOI: 10.1007/978-3-031-32418-5_12
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