Objectifying the Subjective: Cognitive Biases in Topic Interpretations
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Abstract (arXiv)
Interpretation of topics is crucial for their downstream applications. State-of-the-art evaluation measures of topic quality such as coherence and word intrusion do not measure how much a topic facilitates the exploration of a corpus. To design evaluation measures grounded on a task, and a population of users, we do user studies to understand how users interpret topics. We propose constructs of topic quality and ask users to assess them in the context of a topic and provide rationale behind evaluations. We use reflexive thematic analysis to identify themes of topic interpretations from rationales. Users interpret topics based on availability and representativeness heuristics rather than probability. We propose a theory of topic interpretation based on the anchoring-and-adjustment heuristic: users anchor on salient words and make semantic adjustments to arrive at an interpretation. Topic interpretation can be viewed as making a judgment under uncertainty by an ecologically rational user, and hence cognitive biases aware user models and evaluation frameworks are needed.
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References · 16
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- 2023Contextualized Topic Coherence Metricscited by 19
- 2019Towards a Quantum-Like Cognitive Architecture for Decision-Makingcited by 17
4 more
- 2023The ACL OCL Corpus: Advancing Open Science in Computational Linguisticscited by 17
- 2022Are Neural Topic Models Broken?cited by 11
- 2018SOTorrent: Studying the Origin, Evolution, and Usage of Stack Overflow Code Snippetscited by 4
- 2020Cross-Dataset Design Discussion Miningcited by 2
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