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      Four best practices for measuring news sentiment using ‘off-the-shelf’ dictionaries: a large-scale p-hacking experiment

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          Abstract

          We examined the validity of 37 sentiment scores based on dictionary-based methods using a large news corpus and demonstrated 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 suitable 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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          SentiBench - a benchmark comparison of state-of-the-practice sentiment analysis methods

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            THE DICTIONARY OF AFFECT IN LANGUAGE

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              When Communication Meets Computation: Opportunities, Challenges, and Pitfalls in Computational Communication Science

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                Author and article information

                Journal
                CCR
                Computational Communication Research
                Amsterdam University Press
                2665-9085
                2665-9085
                01 March 2021
                : 3
                : 1
                : 1-27
                Article
                CCR2021.1.001.CHAN
                10.5117/CCR2021.1.001.CHAN
                c1c5ad4e-439f-4724-9592-71f32d72850c
                © 2021 Amsterdam University Press

                This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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                Page count
                Pages: 27
                Categories
                Original Articles

                sentiment analysis,p-hacking,validity,news sentiment,agenda setting,text-as-data

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