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Methods for Data Representation

In: Multimodal Affective Computing

Author

Listed:
  • Ramón Zatarain Cabada

    (Instituto Tecnológico de Culiacán)

  • Héctor Manuel Cárdenas López

    (Instituto Tecnológico de Culiacán)

  • Hugo Jair Escalante

    (Instituto Nacional de Astrofísica)

Abstract

This chapter describes the different methods for data representation in sentiment analysis from text. The chapter starts with an introduction to preprocessing algorithms commonly used for data preparation. Afterward, tokenization techniques used in sentiment analysis and natural language processing for representing text-based data into vectors are described. Next, the parsing technique for data representation, diving into a parsing tree to represent a sentence, is discussed, followed by the difference between stemming and lemmatization as partial representations of text joined with tokenization for another type of text-based data representation. Finally, this section describes word embeddings, some of the algorithms used in this representation technique, and some conclusions on preparing data through data representation for ML and DL model training in sentiment analysis. The goal of this section is to introduce the reader to a number of data representation techniques that can be implemented in text-based sentiment analysis.

Suggested Citation

  • Ramón Zatarain Cabada & Héctor Manuel Cárdenas López & Hugo Jair Escalante, 2023. "Methods for Data Representation," Springer Books, in: Multimodal Affective Computing, chapter 0, pages 55-65, Springer.
    • Handle: RePEc:spr:sprchp:978-3-031-32542-7_5
    DOI: 10.1007/978-3-031-32542-7_5
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