IS

Oh, Onook

Topic Weight Topic Terms
0.427 e-government collective sociomaterial material institutions actors practice particular organizational routines practices relations mindfulness different analysis
0.264 media social content user-generated ugc blogs study online traditional popularity suggest different discourse news making
0.229 financial crisis reporting report crises turnaround intelligence reports cash forecasting situations time status adequately weaknesses
0.186 social networks influence presence interactions network media networking diffusion implications individuals people results exchange paper
0.152 information processing needs based lead make exchange situation examined ownership analytical improved situations changes informational

Focal Researcher     Coauthors of Focal Researcher (1st degree)     Coauthors of Coauthors (2nd degree)

Note: click on a node to go to a researcher's profile page. Drag a node to reallocate. Number on the edge is the number of co-authorships.

Agrawal, Manish 1 Eom, Chanyoung 1 Rao, H. Raghav 1 Rao, H. R. 1
2011 Egypt Revolution 1 community intelligence 1 collective sense making 1 hashtag 1
human-machine collaborative information process 1 rumor theory 1 social crisis 1 social information processing 1
social reporting 1 social media 1 social change 1 sociomateriality 1
Twitter 1

Articles (2)

Research Note ‹Role of Social Media in Social Change: An Analysis of Collective Sense Making During the 2011 Egypt Revolution (Information Systems Research, 2015)
Authors: Abstract:
    This study explores the role of social media in social change by analyzing Twitter data collected during the 2011 Egypt Revolution. Particular attention is paid to the notion of collective sense making, which is considered a critical aspect for the emergence of collective action for social change. We suggest that collective sense making through social media can be conceptualized as human-machine collaborative information processing that involves an interplay of signs, Twitter grammar, humans, and social technologies. We focus on the occurrences of hashtags among a high volume of tweets to study the collective sense-making phenomena of milling and keynoting. A quantitative Markov switching analysis is performed to understand how the hashtag frequencies vary over time, suggesting structural changes that depict the two phenomena. We further explore different hashtags through a qualitative content analysis and find that, although many hashtags were used as symbolic anchors to funnel online users' attention to the Egypt Revolution, other hashtags were used as part of tweet sentences to share changing situational information. We suggest that hashtags functioned as a means to collect information and maintain situational awareness during the unstable political situation of the Egypt Revolution.
COMMUNITY INTELLIGENCE AND SOCIAL MEDIA SERVICES: A RUMOR THEORETIC ANALYSIS OF TWEETS DURING SOCIAL CRISES. (MIS Quarterly, 2013)
Authors: Abstract:
    Recent extreme events show that Twitter, a micro-blogging service, is emerging as the dominant social reporting tool to spread information on social crises. It is elevating the online public community to the status of first responders who can collectively cope with social crises. However, at the same time, many warnings have been raised about the reliability of community intelligence obtained through social reporting by the amateur online community. Using rumor theory, this paper studies citizen-driven information processing through Twitter services using data from three social crises: the Mumbai terrorist attacks in 2008, the Toyota recall in 2010, and the Seattle café shooting incident in 2012. We approach social crises as communal efforts for community intelligence gathering and collective information processing to cope with and adapt to uncertain external situations. We explore two issues: (1) collective social reporting as an information processing mechanism to address crisis problems and gather community intelligence, and (2) the degeneration of social reporting into collective rumor mills. Our analysis reveals that information with no clear source provided was the most important, personal involvement next in importance, and anxiety the least yet still important rumor causing factor on Twitter under social crisis situations.