Evaluation on social media user's knowledge behavior model

Daphna Shwartz-Asher, Soon Ae Chun, Nabil R. Adam

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Social media platform allow users to exercise their communication strategies for knowledge creation, sharing and dissemination, which can be use by government agencies as an opportunity to better serve their citizens. In this study, we examine the users' perspective of the Social Media User Behavior Model allowing investigating the social media-based knowledge creation, framing and targeting behaviors by different user types. 123 subjects responded to our Social Media Questionnaire, allowing us to measure perspectives of their social media usage (Preferences, Intensity and Functionality) as well as perspectives of their knowledge behaviors (creation, framing and targeting). The findings imply that users' perspectives support the Social Media User Behavior Model by supporting H1 and H3, connecting the knowledge behaviors targeting and creating to users' characteristics, especially social media Intensity and Functionality. The results means that decision makers can improve communication with the public by identifying social media intensive users and users that use social media for many (versus few) functions, and facilitate different information strategies management for different users types.

Original languageEnglish (US)
Title of host publicationDG.O 2017 - Proceedings of the 18th Annual International Conference on Digital Government Research
Subtitle of host publicationInnovations and Transformations in Government
EditorsCharles C. Hinnant, Adegboyega Ojo
PublisherAssociation for Computing Machinery
Pages590-591
Number of pages2
ISBN (Electronic)9781450353175
DOIs
StatePublished - Jun 7 2017
Event18th Annual International Conference on Digital Government Research, DG.O 2017 - Staten Island, United States
Duration: Jun 7 2017Jun 9 2017

Publication series

NameACM International Conference Proceeding Series
VolumePart F128275

Other

Other18th Annual International Conference on Digital Government Research, DG.O 2017
Country/TerritoryUnited States
CityStaten Island
Period6/7/176/9/17

All Science Journal Classification (ASJC) codes

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

Keywords

  • Knowledge creation
  • Knowledge framing
  • Knowledge targeting
  • Social media
  • Survey
  • User behavior

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