Gianluca Demartini

136 papers receiving 2.2k citations

Hit Papers

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Peers

Gianluca Demartini
Comparison fields: 5 of 113
  • Artificial Intelligence 1.3k
  • Computer Science Applications 1.2k
  • Information Systems 591
  • Management Science and Operations Research 510
  • Sociology and Political Science 395
Replace Matthew Lease with:
Matthew Lease United States
Djellel Difallah Switzerland
Ujwal Gadiraju Netherlands
Stefano Mizzaro Italy
Leif Azzopardi United Kingdom
Erik Duval Belgium
Yoram Bachrach United Kingdom
Michael D. Ekstrand United States
Min Zhang China
Ashton Anderson Canada
Gianluca Demartini relative to Matthew Lease United States Matthew Lease's profile →
Citations per field
00.5×1.5×2.3×
Matthew Lease · 1×
Citations per year

Countries citing papers authored by Gianluca Demartini

Since Specialization
Citations

This map shows the geographic impact of Gianluca Demartini'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 Gianluca Demartini with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gianluca Demartini more than expected).

Fields of papers citing papers by Gianluca Demartini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gianluca Demartini. 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 Gianluca Demartini. The network helps show where Gianluca Demartini may publish in the future.

Co-authorship network of co-authors of Gianluca Demartini

This figure shows the co-authorship network connecting the top 25 collaborators of Gianluca Demartini. A scholar is included among the top collaborators of Gianluca Demartini 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 Gianluca Demartini. Gianluca Demartini 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 1
3 2
4 0
5 3
6 0
7 18
8 7
9 0
10 0
11 63
12 6
13 15
14 39
15
Using Twitter for Insights into the 2009 Swine Flu and 2014 Ebola Outbreaks
2
16
CrowdQ: Crowdsourced Query Understanding
23
17 2
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ARES: A Retrieval Engine based on Sentiments: sentiment-based search result annotation and diversification
7
19
Time based tag recommendation using direct and extended users sets
5
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Finding experts on the semantic desktop
2

About Gianluca Demartini

Gianluca Demartini is a scholar working on Computer Science Applications, Artificial Intelligence and Management Science and Operations Research, having authored 156 papers that have together received 2.3k indexed citations. Recurring topics across this work include Mobile Crowdsensing and Crowdsourcing (61 papers), Topic Modeling (30 papers) and Misinformation and Its Impacts (22 papers). The work is most often cited by research in Computer Science Applications (1.2k citations), Management Science and Operations Research (510 citations) and Artificial Intelligence (1.3k citations). Gianluca Demartini has collaborated with scholars based in Australia, United Kingdom and Germany. Frequent co-authors include Philippe Cudré-Mauroux, Djellel Difallah, Ujwal Gadiraju, Michele Catasta, Alessandro Checco, Stefan Dietze, Ricardo Kawase, Stefano Mizzaro, Kevin Roitero and Eddy Maddalena. Their work appears in journals such as Communications of the ACM, Computers & Education and IEEE Transactions on Knowledge and Data Engineering.

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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