Four best practices for measuring news sentiment using ‘off-the-shelf’ dictionaries: a large-scale p-hacking experiment
Keywords:
sentiment analysis, p-hacking, news sentiment, agenda setting, text-as-data, validityAbstract
We examined the validity of 37 sentiment indicators based on dictionary-based methods using a large news corpus and demonstrate the risk of generating a spectrum of results with different levels of statistical significance by presenting an analysis of relationships between news sentiment and U.S. presidential approval. We summarize our findings into four best practices: 1) use a theory-informed sentiment dictionary; 2) do not assume that the validity and reliability of the dictionary is ‘built-in’; 3) check for the influence of content length and 4) do not use multiple dictionaries to test the same statistical hypothesis.
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Published
2021-04-13
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Chan, C.- hong, Bajjalieh, J., Auvil, L., Wessler, H., Althaus, S., Welbers, K., van Atteveldt, W., & Jungblut, M. (2021). Four best practices for measuring news sentiment using ‘off-the-shelf’ dictionaries: a large-scale p-hacking experiment. Computational Communication Research, 3(1), 1–27. Retrieved from https://computationalcommunication.org/ccr/article/view/40
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