What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- The Internet
- Software
His primary areas of study are Knowledge management, Decision support system, Electronic meeting system, Engineering management and Information technology.
In the field of Knowledge management, his study on Knowledge sharing overlaps with subjects such as Support system.
His study in Decision support system is interdisciplinary in nature, drawing from both Domain, Task, Variety, Software and Process management.
His Electronic meeting system study combines topics in areas such as Field, Component and Operations research.
In his study, Facilitator is strongly linked to IBM, which falls under the umbrella field of Engineering management.
His work deals with themes such as Emergent curriculum, Curriculum mapping and Videoconferencing, which intersect with Information technology.
His most cited work include:
- Electronic meeting systems (1625 citations)
- Systems development in information systems research (922 citations)
- Information technology to support electronic meetings (741 citations)
What are the main themes of his work throughout his whole career to date?
Jay F. Nunamaker focuses on Knowledge management, Deception, Decision support system, Human–computer interaction and Management information systems.
Jay F. Nunamaker is interested in Collaborative software, which is a branch of Knowledge management.
His research integrates issues of Computer security, Cognitive psychology and Artificial intelligence in his study of Deception.
His Artificial intelligence research incorporates themes from Machine learning and Natural language processing.
Jay F. Nunamaker interconnects Intelligent decision support system, Software, Decision analysis and Process management in the investigation of issues within Decision support system.
His studies in Process integrate themes in fields like Quality and Software engineering.
He most often published in these fields:
- Knowledge management (29.82%)
- Deception (15.37%)
- Decision support system (13.76%)
What were the highlights of his more recent work (between 2007-2021)?
- Deception (15.37%)
- Knowledge management (29.82%)
- Credibility (4.13%)
In recent papers he was focusing on the following fields of study:
Deception, Knowledge management, Credibility, Computer security and Human–computer interaction are his primary areas of study.
His Deception research is multidisciplinary, incorporating perspectives in Cognitive psychology, Set, Affect and Artificial intelligence.
His Knowledge management research includes elements of Value, Field, Information overload and Data science.
Jay F. Nunamaker has researched Computer security in several fields, including Internet privacy and Profiling.
His Human–computer interaction research is multidisciplinary, relying on both Interactive kiosk, Brainstorming and Embodied cognition.
The study incorporates disciplines such as Task and Decision analysis in addition to Decision support system.
Between 2007 and 2021, his most popular works were:
- Curriculum Guidelines for Undergraduate Degree Programs in Information Systems (407 citations)
- Embodied Conversational Agent-Based Kiosk for Automated Interviewing (187 citations)
- Detecting fake websites: the contribution of statistical learning theory (124 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- The Internet
- Operating system
Jay F. Nunamaker mainly investigates Credibility, Deception, Computer security, Human–computer interaction and Knowledge management.
His Deception research is multidisciplinary, relying on both Cognitive psychology, Decision support system, Artificial intelligence and Affect.
His study explores the link between Decision support system and topics such as Word count that cross with problems in Cognitive load.
His Artificial intelligence study combines topics in areas such as Variables and Natural language processing.
He has included themes like Social psychology, Embodied agent, Embodied cognition and Sensor fusion in his Human–computer interaction study.
His Knowledge management research incorporates elements of Experiential learning, Expert system and Information overload.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
