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On commenting behavior of Facebook users

Published: 01 May 2013 Publication History

Abstract

Facebook treats friends as a single homogeneous group even though people on Facebook are possibly acquainted with diverse group of individuals and perceive their friends as representatives of different groups. It is a common observation that people tend to select friends with similar characteristics or individuals are likely to change their attributes to conform to their friends. In this measurement study we quantify the extension of this behavior on Facebook. We measure the probability with which a friend belonging to a particular group of friends will or will not comment on a post that has already received comments from other friends belonging/not belonging to his own circle of friends. To this end we collected an original data set of Facebook profiles of 50 volunteers. Our data analysis shows that Facebook users are influenced in their choice of posting comments on friends' wall posts, based on whether or not they are acquainted with the people that left earlier comments. Identification of such behavioral nuances can be helpful in improving the user interface design of online social networks.

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    cover image ACM Conferences
    HT '13: Proceedings of the 24th ACM Conference on Hypertext and Social Media
    May 2013
    275 pages
    ISBN:9781450319676
    DOI:10.1145/2481492
    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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    Publication History

    Published: 01 May 2013

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    Author Tags

    1. Facebook
    2. commenting behavior
    3. communities
    4. homophily

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    HT '13 Paper Acceptance Rate 16 of 96 submissions, 17%;
    Overall Acceptance Rate 378 of 1,158 submissions, 33%

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    Cited By

    View all
    • (2023)The Use of Online Social Networks: Comparing Moroccan and French Communities on FacebookArtificial Intelligence and Smart Environment10.1007/978-3-031-26254-8_129(890-895)Online publication date: 8-Mar-2023
    • (2022)Promoting and countering misinformation during Australia’s 2019–2020 bushfires: a case study of polarisationSocial Network Analysis and Mining10.1007/s13278-022-00892-x12:1Online publication date: 24-Jun-2022
    • (2020)#ArsonEmergency and Australia’s “Black Summer”: Polarisation and Misinformation on Social MediaDisinformation in Open Online Media10.1007/978-3-030-61841-4_11(159-173)Online publication date: 19-Oct-2020
    • (2019)Bayesian inference of private social network links using prior information and propagated dataJournal of Parallel and Distributed Computing10.1016/j.jpdc.2018.11.003125(72-80)Online publication date: Mar-2019
    • (2017)Roman-txtProceedings of the 19th International Conference on Human-Computer Interaction with Mobile Devices and Services10.1145/3098279.3098552(1-9)Online publication date: 4-Sep-2017
    • (2017)Situational determinants of cognitive, affective, and compassionate empathy in naturalistic digital interactionsComputers in Human Behavior10.1016/j.chb.2016.11.02468:C(137-148)Online publication date: 1-Mar-2017
    • (2016)Understanding call logs of smartphone users for making future callsProceedings of the 18th International Conference on Human-Computer Interaction with Mobile Devices and Services10.1145/2935334.2935350(483-490)Online publication date: 6-Sep-2016
    • (2016)Investigating Link Inference in Partially Observable Networks: Friendship Ties and InteractionIEEE Transactions on Computational Social Systems10.1109/TCSS.2016.26189983:3(113-119)Online publication date: Sep-2016

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