research-article

Emotional States vs. Emotional Words in Social Media

Authors:

Winter MasonAuthors Info & Claims

WebSci '15: Proceedings of the ACM Web Science Conference

Article No.: 31, Pages 1 - 10

https://doi.org/10.1145/2786451.2786473

Published: 28 June 2015 Publication History

Abstract

A number of social media studies have equated people's emotional states with the frequency with which they use affectively positive and negative words in their posts. We explore how such word frequencies relate to a ground truth measure of both positive and negative emotion for 515 Facebook users and 448 Twitter users. We find statistically significant but very weak (ρ in the 0.1 to 0.2 range) correlations between positive and negative emotion-related words from the Linguistic Inquiry Word Count (LIWC) dictionary and a well-validated scale of trait emotionality called the Positive and Negative Affect Schedule (PANAS). We test this for tweets and Facebook status updates, focus on different time slices around the completion of the survey, and consider participants who report expressing emotions frequently on social media. With rare exception, this pattern of low correlation persists, suggesting that for the typical user, dictionary-based sentiment analysis tools may not be sufficient to infer how they truly feel.

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Cited By

Ng LLim ALee RChua TNgo CKumar RLauw HKa-Wei Lee R(2024)Love-Hate Dataset: A Multi-Modal Multi-Platform Dataset Depicting Emotions in the 2023 Israel-Hamas WarCompanion Proceedings of the ACM Web Conference 202410.1145/3589335.3651966(1807-1815)Online publication date: 13-May-2024
https://dl.acm.org/doi/10.1145/3589335.3651966
Goodings LEllis DTucker IGoodings LEllis DTucker I(2024)Mental Health and Virtual Companions: The Example of ReplikaUnderstanding Mental Health Apps10.1007/978-3-031-53911-4_3(43-58)Online publication date: 4-Apr-2024
https://doi.org/10.1007/978-3-031-53911-4_3
Yeomans MBoland FCollins HAbi-Esber NBrooks A(2023)A Practical Guide to Conversation Research: How to Study What People Say to Each OtherAdvances in Methods and Practices in Psychological Science10.1177/251524592311839196:4Online publication date: 13-Nov-2023
https://doi.org/10.1177/25152459231183919
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Index Terms

Emotional States vs. Emotional Words in Social Media
1. Applied computing
  1. Law, social and behavioral sciences
2. Human-centered computing
  1. Human computer interaction (HCI)

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cover image ACM Conferences

WebSci '15: Proceedings of the ACM Web Science Conference

June 2015

366 pages

ISBN:9781450336727

DOI:10.1145/2786451

Conference Chair:
David De Roure,
Program Chairs:
Pete Burnap,
Susan Halford

Copyright © 2015 ACM.

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Published: 28 June 2015

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Cited By

Ng LLim ALee RChua TNgo CKumar RLauw HKa-Wei Lee R(2024)Love-Hate Dataset: A Multi-Modal Multi-Platform Dataset Depicting Emotions in the 2023 Israel-Hamas WarCompanion Proceedings of the ACM Web Conference 202410.1145/3589335.3651966(1807-1815)Online publication date: 13-May-2024
https://dl.acm.org/doi/10.1145/3589335.3651966
Goodings LEllis DTucker IGoodings LEllis DTucker I(2024)Mental Health and Virtual Companions: The Example of ReplikaUnderstanding Mental Health Apps10.1007/978-3-031-53911-4_3(43-58)Online publication date: 4-Apr-2024
https://doi.org/10.1007/978-3-031-53911-4_3
Yeomans MBoland FCollins HAbi-Esber NBrooks A(2023)A Practical Guide to Conversation Research: How to Study What People Say to Each OtherAdvances in Methods and Practices in Psychological Science10.1177/251524592311839196:4Online publication date: 13-Nov-2023
https://doi.org/10.1177/25152459231183919
Külz JSpitz AAbu-Akel AGünnemann SWest R(2023)United States politicians’ tone became more negative with 2016 primary campaignsScientific Reports10.1038/s41598-023-36839-113:1Online publication date: 28-Jun-2023
https://doi.org/10.1038/s41598-023-36839-1
Zhu HZheng ZSoleymani MNevatia R(2022)Self-Supervised Learning for Sentiment Analysis via Image-Text MatchingICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)10.1109/ICASSP43922.2022.9747819(1710-1714)Online publication date: 23-May-2022
https://doi.org/10.1109/ICASSP43922.2022.9747819
Horner CGalletta DCrawford JShirsat A(2022)Emotions: The Unexplored Fuel of Fake News on Social MediaJournal of Management Information Systems10.1080/07421222.2021.199061038:4(1039-1066)Online publication date: 2-Jan-2022
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Pellert MMetzler HMatzenberger MGarcia D(2022)Validating daily social media macroscopes of emotionsScientific Reports10.1038/s41598-022-14579-y12:1Online publication date: 4-Jul-2022
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O’Dea BBoonstra TLarsen MNguyen TVenkatesh SChristensen H(2021)The relationship between linguistic expression in blog content and symptoms of depression, anxiety, and suicidal thoughts: A longitudinal studyPLOS ONE10.1371/journal.pone.025178716:5(e0251787)Online publication date: 19-May-2021
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Fong ARoozenbeek JGoldwert DRathje Svan der Linden S(2021)The language of conspiracy: A psychological analysis of speech used by conspiracy theorists and their followers on TwitterGroup Processes & Intergroup Relations10.1177/136843022098759624:4(606-623)Online publication date: 31-May-2021
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Ming YMatteson MSun J(2021)Reddit use in the LIS communityJournal of Librarianship and Information Science10.1177/09610006211052084(096100062110520)Online publication date: 19-Oct-2021
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