Jim Samuel

Mentions HPC has been widely used in CS & other computation intensive disciplines, but has remained largely siloed away from the vast array of social & economics disciplines. Elaborates that with ubiquitous big data, there is a compelling need to make HPC technologically & economically accessible, easy to use, & operationally democratized. Created By

Performs sentiment analytics on vaccine tweets, studied changes in public sentiment over time. Analyzes social media dating from early February 2021 and late March 2021 which shows that in spite of overall strength of positive sentiment and increasing numbers of Americans being fully vaccinated, negative sentiment about COVID-19 vaccines still persists among sections of people who are still hesitant towards the vaccine.

Collects and analyzes stock market activity for stocks such as GameStop, AMC, KOSS, and Nokia, then retrieve posts from Reddit to determine whether or not these activities could be predicted as well as determine when a critical mass was obtained to successfully execute these stock trades.

Employs the application of artificially intelligence methods to model the phenomenon of virality of social media posts, leading to a process and methodological innovation which enables the dynamic generation of words and sequences with a high likelihood of viral popularity on social  media.

Focuses on addressing a segment of the broader problem described above by applying multiple surprised and unsupervised and unsupervised machine learning methods to explore the behavior of TDD by (i) topical alignment, and (ii) by sentiment alignment.

Discusses the various dynamics surrounding informatics stimulated electronic markets and argues that increased richness of information dimensions will not necessarily improve market efficiency.

Bases on economic experiments which simulated electronic trading markets to study the effects of technology driven information artifacts and the study demonstrated the influence of information signals on human behavior and stock trading performance.

Presents findings from an exploratory analysis and outlines a framework to gain insights into educational factors in the emerging technology waves influencing the role of, and impact upon, women. Identifies 'ways for learning' and "self-efficacy' as key factors, which together lead us to 'Advancement of Women in Technology' (AWT) insights framework.

Identifies the increase of fear as the severity of COVID-19 becomes evident, and uses machine learning methods for the classification of Twitter data and generates public sentiment insights with a wide range of pandemic information management implications.

Uses machine learning (ML) techniques for behavioral finance categories in addressing behavioral aspects in Financial Big Data (FBD). Discusses how the ontological feasibility of such an approach is presented and the primary purpose of this study is propositioned: ML based behavioral models can effectively estimate informational performance categories in FBD.

Investigates the dynamics and characteristics of dominance in virtual interaction by analyzing electronic chat transcripts of groups solving a hidden profile task.