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Vlogging Over Time: Longitudinal Impressions and Behavior in YouTube

Published: 25 November 2018 Publication History

Abstract

YouTube vlogging, as a popular genre of ubiquitous social video, engages people in entertainment, civic, and social activities. Although several aspects of vlogging have been studied in media studies and multimedia analysis, the longitudinal angle of vlogging regarding recognition of personal state and trait impressions from behavior has not been yet analyzed. We present a study using behavioral data of vloggers who posted vlogs on YouTube for a period between three and six years. We use online crowdsourcing to collect a rich set of 21 impression variables for each video, including perceived personality, mood, skills, and expertise. Acoustic and motion features are extracted to characterize basic nonverbal behavior. The analysis shows that only a couple of perceived variables, including perceived expertise and perceived quality of audio and video, display weak temporal patterns. Furthermore, we show that the use of longitudinal data helps to improve the automatic inference of impressions for several of the impression variables.

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  • (2024)Proselytizing the potential of influencer marketing via artificial intelligence: mapping the research trends through bibliometric analysisCogent Business & Management10.1080/23311975.2024.237288911:1Online publication date: Jul-2024
  • (2024)How self-disclosure builds cancer communities through authentic stories on YouTubeComputers in Human Behavior10.1016/j.chb.2024.108226156:COnline publication date: 9-Jul-2024
  • (2024)Multimodal Unsupervised Domain Adaptation for Predicting Speaker Characteristics from VideoSN Computer Science10.1007/s42979-024-02723-65:5Online publication date: 11-May-2024
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  1. Vlogging Over Time: Longitudinal Impressions and Behavior in YouTube

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    cover image ACM Other conferences
    MUM '18: Proceedings of the 17th International Conference on Mobile and Ubiquitous Multimedia
    November 2018
    548 pages
    ISBN:9781450365949
    DOI:10.1145/3282894
    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 the author(s) 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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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 25 November 2018

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    Author Tags

    1. YouTube
    2. behavior
    3. impressions
    4. social media
    5. vlog

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    MUM '18 Paper Acceptance Rate 37 of 82 submissions, 45%;
    Overall Acceptance Rate 190 of 465 submissions, 41%

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    Cited By

    View all
    • (2024)Proselytizing the potential of influencer marketing via artificial intelligence: mapping the research trends through bibliometric analysisCogent Business & Management10.1080/23311975.2024.237288911:1Online publication date: Jul-2024
    • (2024)How self-disclosure builds cancer communities through authentic stories on YouTubeComputers in Human Behavior10.1016/j.chb.2024.108226156:COnline publication date: 9-Jul-2024
    • (2024)Multimodal Unsupervised Domain Adaptation for Predicting Speaker Characteristics from VideoSN Computer Science10.1007/s42979-024-02723-65:5Online publication date: 11-May-2024
    • (2022)First Impressions: A Survey on Vision-Based Apparent Personality Trait AnalysisIEEE Transactions on Affective Computing10.1109/TAFFC.2019.293005813:1(75-95)Online publication date: 1-Jan-2022
    • (2021)On the Effect of Observed Subject Biases in Apparent Personality Analysis From Audio-Visual SignalsIEEE Transactions on Affective Computing10.1109/TAFFC.2019.295603012:3(607-621)Online publication date: 1-Jul-2021
    • (2019)BookTubing Across Regions: Examining Differences Based on Nonverbal and Verbal CuesProceedings of the 2019 ACM International Conference on Interactive Experiences for TV and Online Video10.1145/3317697.3323357(145-156)Online publication date: 4-Jun-2019

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