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Jim Samuel

Associate Professor & Executive Director, Informatics, Rutgers University-New Brunswick

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About Jim

Dr. Samuel’s primary research focuses on human intelligence & artificial intelligence interaction, information philosophy, NLP NLU NLG, language, sentiment analysis & informatics – research on current events including COVID-19 & vaccine public opinion & public policy, Overarching themes in Dr. Samuel’s writings include: Applications of AI, AI Bias & Ethics, Machine Learning, Quantitative /Financial /Econ modeling, behavioral finance, social media & behavioral finance /investing, AI education, gender bias. Dr. Samuel’s serves in editorial roles for scholarly Journals & advises corporations & non-profits on AI, innovation & strategy. Expertise

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"Would You Please Like My Tweet?! An Artificially Intelligent, Generative Probabilistic, and Econometric Based System Design for Popularity-Driven Tweet Content Generation" (with Myles D.Garvey and Alexander Pelaez). Decision Support Systems 144 (2021).

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.

"Textual Data Distributions: Kullback Leibler Textual Distributions Contrasts on GPT-2 Generated Texts with Supervised, Unsupervised Learning on Vaccine & Market Topics & Sentiment" (2021).

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.

"Strategies for Democratization of Supercomputing: Availability, Accessibility and Usability of High Performance Computing for Education and Practice of Big Data Analytics" (with Margaret Brennan-Tonetta, Yana Samuel, Pradeep Subed, and Jack Smith). Computers and Society (2021).

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

"Public Perceptions of COVID-19 Vaccines: Policy Implications from US Spatiotemporal Sentiment Analytics," (with G.G. Md. Nawaz Ali, MD Mokhlesur Rahman, Amjad Hossain, Md. Shahinoor Rahman, Kamal Chandra Paul, and Jean-Claude Thill), Healthcare, September 27, 2021.

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.

"David and Goliath Revisited: How small investors are changing the landscapes of financial markets," (with Alexander Palaez and Elaine R. Winston), Northeast Decision Sciences Institute, April 9, 2021.

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.

"Informatics in Information Richness: A Market Mover? An Examination of Information Richness in Electronic Markets," International Institute of Info, December 15, 2020.

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

"Beyond STEM, How Can Women Engage Big Data, Analytics, Robotics and Artificial Intelligence? An Exploratory Analysis of Confidence and Educational Factors in the Emerging Technology Waves Influencing the Role of, and Impact Upon, Women" (with j. George and Y. Samuel). Assoc. Professor & Exec. Director, Informatics (2020).

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.

"The Effects Of Technology Driven Information Categories On Performance In Electronic Trading Markets" (with Richard Holowczak and Alexander Pelaez). adsab (2020).
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.
"COVID-19 Public Sentiment Insights and Machine Learning for Tweets Classification" (with G. G. Md. Nawaz Ali, Md. Mokhlesur Rahman, Ek Esawi, and Yana Samuel). Cornell University (2020).

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.

"Information Token Driven Machine Learning For Electronics Markets: Performance Effects In Behavioral Financial Big Data " Journal of Information Systems and Technology Management – 14, no. 3 (2017): 371–383.

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.

"Automating Discovery of Dominance in Synchronus Computer-Mediated Communication," (with Richard Holowczak, Raquel Benbunan-Fich, and Llan Levine), 47th Hawaii International Conference on System Sciences, 2014.

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