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Who is More Positive in Private? Analyzing Sentiment Differences across Privacy Levels and Demographic Factors in Facebook Chats and Posts

Published: 25 August 2015 Publication History

Abstract

Understanding users' sentiments in social media is important in many domains, such as marketing and online applications. Is one demographic group inherently different from another? Does a group express the same sentiment both in private and public? How can we compare the sentiments of different groups composed of multiple attributes? In this paper, we take an interdisciplinary approach towards mining the patterns of textual sentiments and metadata. First, we look into several existing hypotheses in social science on the interplay between user characteristics and sentiments, as well as the related evidence in the field of social network data analysis. Second, we present a dataset with unique features (Facebook users' chats and posts in multiple languages) and a procedure to process the data. Third, we test our hypotheses on this dataset and interpret the results. Fourth, under the subgroup-discovery paradigm, we present an approach with two algorithms that generalizes single-attribute testing. This approach provides more detailed insight into the relationships among attributes, and reveals interesting attribute-value combinations with distinct sentiments. Furthermore, it offers novel hypotheses for examination in future studies.

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  1. Who is More Positive in Private? Analyzing Sentiment Differences across Privacy Levels and Demographic Factors in Facebook Chats and Posts

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      cover image ACM Conferences
      ASONAM '15: Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2015
      August 2015
      835 pages
      ISBN:9781450338547
      DOI:10.1145/2808797
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      Published: 25 August 2015

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      • the Flemish Agency for Innovation through Science and Technology (IWT)
      • the organization Fund for Scientific Research for Flanders (FWO)

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      • (2023)Getting Meta: A Multimodal Approach for Detecting Unsafe Conversations within Instagram Direct Messages of YouthProceedings of the ACM on Human-Computer Interaction10.1145/35796087:CSCW1(1-30)Online publication date: 16-Apr-2023
      • (2022)Predicting and Analyzing Privacy Settings and Categories for Posts on Social Media2022 IEEE International Conference on Big Data (Big Data)10.1109/BigData55660.2022.10020677(5692-5697)Online publication date: 17-Dec-2022
      • (2020)How Do You Feel OnlineProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/34322234:4(1-32)Online publication date: 18-Dec-2020
      • (2020)Exploring the social broadcasting crisis communication: insights from the mars recall scandalEnterprise Information Systems10.1080/17517575.2020.176502315:3(420-443)Online publication date: 28-Jun-2020
      • (2017)Social media engagement analysis of U.S. Federal health agencies on FacebookBMC Medical Informatics and Decision Making10.1186/s12911-017-0447-z17:1Online publication date: 21-Apr-2017
      • (2017)Current State of Text Sentiment Analysis from Opinion to Emotion MiningACM Computing Surveys10.1145/305727050:2(1-33)Online publication date: 25-May-2017
      • (2017)Friends are forever? Evolution of active friendship clusters in online social networks2017 9th International Conference on Communication Systems and Networks (COMSNETS)10.1109/COMSNETS.2017.7945453(558-563)Online publication date: Jan-2017

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