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Social and Behavioral Sciences Commons™
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Articles 1 - 3 of 3
Full-Text Articles in Social and Behavioral Sciences
Detecting, Modeling, And Predicting User Temporal Intention, Hany M. Salaheldeen
Detecting, Modeling, And Predicting User Temporal Intention, Hany M. Salaheldeen
Computer Science Theses & Dissertations
The content of social media has grown exponentially in the recent years and its role has evolved from narrating life events to actually shaping them. Unfortunately, content posted and shared in social networks is vulnerable and prone to loss or change, rendering the context associated with it (a tweet, post, status, or others) meaningless. There is an inherent value in maintaining the consistency of such social records as in some cases they take over the task of being the first draft of history as collections of these social posts narrate the pulse of the street during historic events, protest, riots, …
Characteristics Of Social Media Stories, Yasmin Ainoamany, Michele C. Weigle, Michael L. Nelson
Characteristics Of Social Media Stories, Yasmin Ainoamany, Michele C. Weigle, Michael L. Nelson
Computer Science Faculty Publications
An emerging trend in social media is for users to create and publish "stories", or curated lists of web resources with the purpose of creating a particular narrative of interest to the user. While some stories on the web are automatically generated, such as Facebook’s "Year in Review", one of the most popular storytelling services is "Storify", which provides users with curation tools to select, arrange, and annotate stories with content from social media and the web at large. We would like to use tools like Storify to present automatically created summaries of archival collections. To support automatic story creation, …
An Analysis Of User-Generated Comments On The Development Of Social Mobile Learning, Shenghua Zha, Wu He
An Analysis Of User-Generated Comments On The Development Of Social Mobile Learning, Shenghua Zha, Wu He
Information Technology & Decision Sciences Faculty Publications
In this study, the authors used a mixed-method approach to analyze user-generated comments on social mobile learning from three leading news sites that report the latest development in higher education. Koole’s mobile learning model was used to code comments made by the public on the three news sites. Results showed that social mobile learning has gained an increasing public engagement in the past four years. Responders’ discussion in the comments primarily focused on four themes of social mobile learning: technology adoption, effective design, faculty training, and student training. In the end, the authors discussed the implications for developers and educators …