Folk Classification of Social Media Services as Grounds for Explaining or Predicting Trends in Use

被引:0
|
作者
Wilkes, Gilbert [1 ]
Trayor, Brian [2 ]
Hodson, Jaigris [3 ]
机构
[1] Mt Royal Univ, Informat Design, Calgary, AB, Canada
[2] Mt Royal Univ, Fac Commun Studies, Informat Design Program, Calgary, AB, Canada
[3] GCI Canada, Social Media, Toronto, ON, Canada
关键词
Media choice; social media; user experience;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Social media as a class of communication platforms has been investigated in terms of user intentions, or why people use them, in terms of depth or kind of interaction, and in terms of the demographic character of users across various services. There is little understanding however of how and on what grounds people sort the services in which they participate into categories that can explain or predict their patterns of use. One user may sort Twitter.com, Tumblr.com, and Pinterest.com together because of opportunities for interaction, and aggregators like Reddit.com, or StumbleUpon.com because of content. We propose a seed- and-snowball sample that begins with users in two demographic categories, twenty somethings and forty somethings, that asks participants to free pile-sort cards that represent social media services popular in Canada into groups. We will use a short structured interview collected from the initial participants to develop grounds to explain the categorizing criteria the participants demonstrate. We believe the results of the study can explain or predict trends in patterns use, for example the exodus of younger users from Facebook. This is a research work-in-progress though we expect to have results in the form of data and analyses to present at the conference.
引用
收藏
页数:5
相关论文
共 50 条
  • [31] Land use classification from social media data and satellite imagery
    Yaqin Ye
    Ying An
    Bo Chen
    JunJue Wang
    Yingqiang Zhong
    The Journal of Supercomputing, 2020, 76 : 777 - 792
  • [32] Land use classification from social media data and satellite imagery
    Ye, Yaqin
    An, Ying
    Chen, Bo
    Wang, JunJue
    Zhong, Yingqiang
    JOURNAL OF SUPERCOMPUTING, 2020, 76 (02): : 777 - 792
  • [33] Predicting the level of social media use among journalists: machine learning analysis
    Elareshi, Mokhtar
    Al Shami, Ahmad
    Ziani, Abdulkrim
    Chaudhary, Shubhda
    Youssef, Noora
    FRONTIERS IN COMMUNICATION, 2024, 9
  • [34] Predicting Fashion Involvement by Media Use, Social Comparison, and Lifestyle: An Interaction Model
    Sun, Yanshu
    Guo, Steve
    INTERNATIONAL JOURNAL OF COMMUNICATION, 2017, 11 : 4559 - 4582
  • [35] Trends in the Use of Social Media as a Tool of Marketing Communications in FMCG Sector in India
    Banerjee, Baisakhi
    Kumar, Ashwini B. J.
    INTERNATIONAL JOURNAL OF ONLINE MARKETING, 2013, 3 (03) : 62 - 75
  • [36] A Framework Model for Integrating Social Media, the Web, and Proprietary Services Into YouTube Video Classification Process
    Alsafrjalani, Mohamad Hammam
    INTERNATIONAL JOURNAL OF MULTIMEDIA DATA ENGINEERING & MANAGEMENT, 2019, 10 (02): : 21 - 36
  • [37] DECADE OF HEALTH SERVICES - SOCIAL SURVEY TRENDS IN USE AND EXPENDITURE - ANDERSEN,R AND ANDERSON,ON
    CAMPBELL, RR
    AMERICAN ECONOMIC REVIEW, 1968, 58 (04): : 1040 - 1043
  • [38] Predicting the cryptocurrency market using social media metrics and search trends during COVID-19
    Mou, Jian
    Liu, Wenting
    Guan, Chong
    Westland, J. Christopher
    Kim, Jongki
    ELECTRONIC COMMERCE RESEARCH, 2024, 24 (02) : 1307 - 1333
  • [39] An analysis of fear factors predicting enterprise social media use in an era of communication visibility
    Van Zoonen, Ward
    Treem, Jeffrey W.
    Sivunen, Anu
    INTERNET RESEARCH, 2022, 32 (07) : 354 - 375
  • [40] E-ELECTIONEERING 2010: TRENDS IN SOCIAL MEDIA USE IN AUSTRALIAN POLITICAL COMMUNICATION
    Macnamara, Jim
    Kenning, Gail
    MEDIA INTERNATIONAL AUSTRALIA, 2011, (139) : 7 - 22