What is he best known for?
The fields of study he is best known for:
- Statistics
- Social science
- Social psychology
His primary areas of investigation include Exponential random graph models, Random graph, Artificial intelligence, Social network and Discrete mathematics.
His Exponential random graph models research is multidisciplinary, incorporating elements of Goodness of fit, Markov chain Monte Carlo, Psychological resilience and Transitive relation.
In his study, Random variable, Null model, Graphical model and Local area network is strongly linked to Markov chain, which falls under the umbrella field of Random graph.
Garry Robins interconnects Outcome and Friendship in the investigation of issues within Artificial intelligence.
His Social network research focuses on Social psychology and how it connects with Developmental psychology.
Garry Robins focuses mostly in the field of Discrete mathematics, narrowing it down to topics relating to Clustering coefficient and, in certain cases, Relational database and 3-dimensional matching.
His most cited work include:
- An introduction to exponential random graph (p * ) models for social networks (1366 citations)
- NEW SPECIFICATIONS FOR EXPONENTIAL RANDOM GRAPH MODELS (974 citations)
- Recent developments in exponential random graph (p*) models for social networks (616 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Exponential random graph models, Social network, Social psychology, Random graph and Artificial intelligence.
His Exponential random graph models research is multidisciplinary, relying on both Theoretical computer science, Snowball sampling, Econometrics, Statistical model and Markov chain.
His Social network research incorporates themes from Social influence, Management science, Network science and Data science.
His work deals with themes such as Perception and Social cognition, which intersect with Social psychology.
His Random graph research includes elements of Random regular graph, Null model and Random geometric graph.
His studies deal with areas such as Goodness of fit, Machine learning and Dynamic network analysis as well as Artificial intelligence.
He most often published in these fields:
- Exponential random graph models (32.34%)
- Social network (21.56%)
- Social psychology (18.56%)
What were the highlights of his more recent work (between 2013-2021)?
- Exponential random graph models (32.34%)
- Social network (21.56%)
- Theoretical computer science (11.38%)
In recent papers he was focusing on the following fields of study:
Garry Robins mainly focuses on Exponential random graph models, Social network, Theoretical computer science, Environmental governance and Environmental studies.
His Exponential random graph models study combines topics from a wide range of disciplines, such as Snowball sampling, Network model, Inference, Mathematical optimization and Statistical model.
His Statistical model study combines topics in areas such as Sampling, Estimation theory, Markov chain and Markov chain Monte Carlo.
His research integrates issues of Context, English for academic purposes, Network science and Data science in his study of Social network.
His Theoretical computer science study integrates concerns from other disciplines, such as Node, Missing data, Bayesian probability, Random graph and Sample.
Garry Robins integrates many fields in his works, including Random graph and Network analysis.
Between 2013 and 2021, his most popular works were:
- Network structure and institutional complexity in an ecology of water management games (131 citations)
- Doing Social Network Research: Network-based Research Design for Social Scientists (109 citations)
- The impact of injecting networks on hepatitis C transmission and treatment in people who inject drugs (103 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Social science
- Social psychology
His main research concerns Exponential random graph models, Environmental studies, Environmental governance, Management science and Set.
Garry Robins combines subjects such as Interpersonal communication, Knowledge management, Boundary spanning, Artificial intelligence and Machine learning with his study of Exponential random graph models.
His study in the field of Categorization also crosses realms of Network structure.
His Management science research incorporates elements of Context, Network science, Data science and Social network.
His Social network research integrates issues from Graph drawing, Social complexity and Social system.
The Set study combines topics in areas such as Relation and Sustainability.
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