Alessandro Canossa

45 papers receiving 1.2k citations

Peers

Alessandro Canossa
Comparison fields: 5 of 87
  • Sociology and Political Science 687
  • Artificial Intelligence 567
  • Developmental and Educational Psychology 481
  • Computer Vision and Pattern Recognition 293
  • Clinical Psychology 193
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Citations per year

Countries citing papers authored by Alessandro Canossa

Since Specialization
Citations

This map shows the geographic impact of Alessandro Canossa's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Alessandro Canossa with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alessandro Canossa more than expected).

Fields of papers citing papers by Alessandro Canossa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Alessandro Canossa. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Alessandro Canossa. The network helps show where Alessandro Canossa may publish in the future.

Co-authorship network of co-authors of Alessandro Canossa

This figure shows the co-authorship network connecting the top 25 collaborators of Alessandro Canossa. A scholar is included among the top collaborators of Alessandro Canossa based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Alessandro Canossa. Alessandro Canossa is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 24
3 1
4
Like a DNA string: Sequence-based player profiling in Tom Clancy’s the Division
8
5 35
6 12
7
Eliciting Emotions in Design of Games - a Theory Driven Approach.
4
8 8
9
In Your Face(t) Impact of Personality and Context on Gameplay Behavior.
10
10
Games Research Today: Analyzing the Academic Landscape 2000-2014.
35
11
Towards a Procedural Evaluation Technique: Metrics for Level Design.
11
12 5
13
Intro to User Analytics
0
14
Welcome from the organizers
1
15 22
16 67
17 27
18
Cognitive tools for game world designers
1
19
Game Metrics and Biometrics : The Future of Player Experience Research
3
20
Play-Persona: Modeling Player Behaviour in Computer Games
5

About Alessandro Canossa

Alessandro Canossa is a scholar working on Developmental and Educational Psychology, Human-Computer Interaction and Artificial Intelligence, having authored 47 papers that have together received 1.3k indexed citations. Recurring topics across this work include Digital Games and Media (27 papers), Artificial Intelligence in Games (21 papers) and Educational Games and Gamification (18 papers). The work is most often cited by research in Developmental and Educational Psychology (481 citations), Human-Computer Interaction (165 citations) and Artificial Intelligence (567 citations). Alessandro Canossa has collaborated with scholars based in Denmark, United States and Mexico. Frequent co-authors include Anders Drachen, Magy Seif El‐Nasr, Georgios N. Yannakakis, Anders Tychsen, Julian Togelius, Christian Thurau, Rafet Sifa, Christian Bauckhage, Tobias Mahlmann and Kristian Kersting. Their work appears in journals such as Proceedings of the ACM on Human-Computer Interaction, Information Visualization and Surveillance & Society.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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