Mining government tweets to identify and predict citizens engagement-Reference-Cited by-同舟云学术

Mining government tweets to identify and predict citizens engagement

Published:2020-02 Issue: Volume:60 Page:101211
ISSN:0160-791X
Container-title:Technology in Society
language:en
Short-container-title:Technology in Society

Author:

Siyam Nur,Alqaryouti Omar,Abdallah Sherief

Publisher

Elsevier BV

Subject

Sociology and Political Science,Education,Business and International Management,Human Factors and Ergonomics

Reference50 articles.

1. Guidelines for eParticipation and Social Media for Government Entities;UAE mGovernment,2016

2. Bowling Together: Online Public Engagement in Policy Deliberation;Coleman,2001

3. Electronic citizens participation: systematic review;Boudjelida,2016

4. The effect of post type and post category on citizen interaction level on Facebook: the case of metropolitan and provincial municipalities in the Marmara region of Turkey;Sobacı,2018

5. Facebook content strategies and citizens' online engagement: the case of Greek local governments;Lappas;Rev. Socionetw. Strateg.,2018

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