Text Diversity Analysis Task

A Text Diversity Analysis Task is a diversity analysis task focused on evaluating the variety in text items.

• Context:
  • It can be supported by a Text Diversity Analysis System (that implements a text diversity analysis algorithm).
  • It can support the production of unbiased and inclusive language.
  • ...
• Example(s):
  • To evaluate the vocabulary diversity in a collection of news articles.
  • For creative writing course to inspire students to diversify their sentence structures.
  • Lexical Diversity Analysis: Examines the variety of words by counting unique words or calculating lexical density.
  • Syntactic Diversity Analysis: Focuses on the variety of sentence structures by counting different sentence types or calculating syntactic complexity.
  • Semantic Diversity Analysis: Analyzes the variety of topics and concepts by identifying key topics and their interrelations.
  • Discourse Diversity Analysis: Evaluates the variety of discourse styles like argumentation, narration, and description.
  • Pragmatic Diversity Analysis: Investigates the variety of communicative goals through different types of speech acts such as requests, commands, and questions.
  • ...
• Counter-Example(s):
  • Text Classification which categorizes to existing labels.
  • Text Paraphrasing which generates alternative forms of the same text (though it may take a diversity optional input).
• See: Image Diversity Analysis.

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References

2023

• GBard
  • QUOTE: Text Diversity Analysis is the process of assessing the variety of language used in a text. Common types include:
    • Lexical Diversity Analysis: Examines the variety of words by counting unique words or calculating lexical density.
    • Syntactic Diversity Analysis: Focuses on the variety of sentence structures by counting different sentence types or calculating syntactic complexity.
    • Semantic Diversity Analysis: Analyzes the variety of topics and concepts by identifying key topics and their interrelations.
    • Discourse Diversity Analysis: Evaluates the variety of discourse styles like argumentation, narration, and description.
    • Pragmatic Diversity Analysis: Investigates the variety of communicative goals through different types of speech acts such as requests, commands, and questions.
  • The task can be used for multiple purposes, including:
    • Identifying and mitigating biases in language models.
    • Promoting diversity in creative writing.
    • Improving the readability of texts.
    • Analyzing language diversity in various contexts like news articles, social media posts, or academic papers.
  • Overall, it serves as a powerful tool for various purposes including bias mitigation, creative writing enhancement, readability improvement, and contextual language diversity analysis.

2013

• (Bache et al., 2013) ⇒ Kevin Bache, David Newman, and Padhraic Smyth. (2013). “Text-based Measures of Document Diversity.” In: Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ISBN:978-1-4503-2174-7 doi:10.1145/2487575.2487672
  • ABSTRACT: Quantitative notions of diversity have been explored across a variety of disciplines ranging from conservation biology to economics. However, there has been relatively little work on measuring the diversity of text documents via their content. In this paper we present a text-based framework for quantifying how diverse a document is in terms of its content. The proposed approach learns a topic model over a corpus of documents, and computes a distance matrix between pairs of topics using measures such as topic co-occurrence. These pairwise distance measures are then combined with the distribution of topics within a document to estimate each document's diversity relative to the rest of the corpus.

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