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Full-Text Articles in Engineering
Analyzing Responses From Likert Surveys And Risk-Adjusted Ranking: A Data Analytics Perspective, Abhijit Gosavi
Analyzing Responses From Likert Surveys And Risk-Adjusted Ranking: A Data Analytics Perspective, Abhijit Gosavi
Engineering Management and Systems Engineering Faculty Research & Creative Works
We broadly consider the topic of ranking entities from surveys/opinions. Often, numerous ranks from different respondents are available for the same entity, e.g., a candidate from a pool, and yet an averaging of those ranks may not serve the purpose of identifying a consensus candidate. We first consider a risk-adjusted paradigm for ranking, where the rank is defined as the average (mean) rank plus a scalar times the risk in the rank; we use standard deviation as a risk metric. In case of a candidate being ranked either on the basis of opinions of a selection committee's members or on …
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, …
Social Media For Informal Science Learning In China: A Case Study, Ke Zhang, Fei Gao
Social Media For Informal Science Learning In China: A Case Study, Ke Zhang, Fei Gao
Fei Gao
This article reports a case study on a popular informal science learning community via social media in China, named GuoKr (meaning “nutshell” in English). Data were collected through a variety of Chinese social media and social networking sites, web-based community portals, and discussion boards. Content analyses and data mining were conducted to investigate how GuoKr successfully attracted and engaged public in informal learning on scientific topics in particular. The study found three key characteristics that contributed to the success of such learning communities: (a) utilizing a variety of social media to empower participants with just-in-time, accidental learning opportunities; (b) daily …