College of Computer Science and Engineering
Systems Engineering Department
Presents a Seminar on
Integrated Twitter Analysis to Distinguish Systems Thinkers at Various Levels: A Case Study of COVID-19
Date: Tuesday, 1st December, 2020
Time: 4:00 pm – 5:00 pm
Location: MS Teams, Click here to Join
Dr. Harun Pirim
Clinical Assistant Professor
Industrial and Systems Engineering Department
Mississippi State University (MSU)
Although the application of Systems Thinking (ST) has become essential for practitioners and experts when dealing with turbulent and complex environments, there are limited studies available in the extant literature that investigate how the ST skills of experts can be correlated with Twitter analysis. To address this gap, this study uses a social network analysis approach to explore the relationship between experts' ST and their followers' network. Twitter is a crucial medium in circulating the information, and unfortunately, users propagate sometimes erroneous or inadequate messages in a network. Thus, COVID-19 emerged as a relevant case study to investigate the relationship between COVID-19 experts' Twitter network and their systems thinking capabilities. Therefore, a sample of 55 trusted expert Twitter accounts related to COVID-19 has been selected for the current study based on the lists of Forbes, Fortune, and Bustle. Then, the Twitter network of these experts based on features extracted from their twitter accounts, including organic Twitter account metrics, tweets' measures, sentimental analysis, source of tweets as well as their tweets. After clustering the network based on tweets and Twitter features, we found that three distinct groups of experts emerged. For validating the result, we went further and constructed the followers' network of experts. Then, we mapped the system thinking dimensions to followers' network characteristics such as Betweenness centrality, Closeness centrality, Degree centrality, Eigen centralities, and node-level metrics. By comparing the followers' network characteristics of 55 experts, we found that three identified clusters had meaningful differences in centrality scores and node-level metrics. The cluster with a higher, medium, lower score can be classified as Holistic thinkers, Middle thinkers, and Reductionist thinkers, respectfully. In conclusion, this research was testing that the capabilities of individuals as system thinkers can lead to revealing unique network patterns and distinct communities associated with the level of system thinking of COVID-19 experts.
Harun Pirim received his Ph.D. degree in Industrial and Systems Engineering (ISE) from Mississippi State University in 2011. He holds Econometrics (Operations Research concentration) MA and Industrial Engineering BS degrees from Dokuz Eylul University, Turkey. He is currently employed at Mississippi State University (MSU), Industrial and Systems Engineering Department as Clinical Assistant Professor. Prior to joining MSU he worked at KFUPM, Systems Engineering Department. His published work are related to clustering and data mining in general. He is a member of IISE and SIAM.
Harun's recent research focuses on descriptive and predictive network analysis including investigation of distinct network features; machine learning, and mathematical programming aspects of network problems. Some applications, he is currently working are: social media data: twitter network analysis to reveal systems thinking features; gene sequence data: network cluster analysis to predict functions of hypothetical proteins; ADHD brain data: network analysis to generate deep learning features employed in prediction of health condition.
All faculty, researchers and graduate students are invited to attend.
Systems Engineering Department, College of Computer Sciences and Engineering
Telephone: +966 (13) 860 2988, Email: firstname.lastname@example.org, Website: www.kfupm.edu.sa/departments/se/
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