Maria Sokhn

30 papers receiving 501 citations

Hit Papers

The power of a blockchain-based supply chain20192026202120232019100200300

Peers

Maria Sokhn
Comparison fields: 5 of 72
  • Information Systems 382
  • Strategy and Management 175
  • Management Information Systems 154
  • Artificial Intelligence 96
  • Sociology and Political Science 91
Replace Rima Kilany with:
Rima Kilany Lebanon
İ̇hsan Tolga Medeni Türkiye
Shoufeng Cao Australia
An Binh Tran Australia
Jens Strüker Germany
Jiann-Min Yang Taiwan
Yani Shi China
Suling Jia China
Samant Saurabh India
Shafaq Khan United Arab Emirates
Maria Sokhn relative to Rima Kilany Lebanon Rima Kilany's profile →
Citations per field
00.5×4.8×
Rima Kilany · 1×
Citations per year

Countries citing papers authored by Maria Sokhn

Since Specialization
Citations

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

Fields of papers citing papers by Maria Sokhn

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maria Sokhn

This figure shows the co-authorship network connecting the top 25 collaborators of Maria Sokhn. A scholar is included among the top collaborators of Maria Sokhn 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 Maria Sokhn. Maria Sokhn 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
SAMS: Human-in-the-loop approach to combat the sharing of digital misinformation
5
2 0
3 1
4 1
5 2
6 11
7 41
8 1
9 1
10 1
11 0
12
Semantic based auto-completion of business process modelling in egovernment
1
13
Enhancing Business Process modelling for e-Government processes using semantic web technologies and Linked Data principles
0
14 1
15 6
16 0
17 3
18 4
19
Conference knowledge modelling for conference-video-recordings querying and visualization.
1
20
Knowledge Management Framework for Conference Video-recording Retrieval.
2

About Maria Sokhn

Maria Sokhn is a scholar working on Computer Science Applications, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 36 papers that have together received 543 indexed citations. Recurring topics across this work include Semantic Web and Ontologies (12 papers), Mobile Crowdsensing and Crowdsourcing (5 papers) and Spam and Phishing Detection (4 papers). The work is most often cited by research in Management Information Systems (154 citations), Information Systems (382 citations) and Strategy and Management (175 citations). Maria Sokhn has collaborated with scholars based in Switzerland, Lebanon and France. Frequent co-authors include Rima Kilany, Philippe Cudré-Mauroux, Elena Mugellini, Omar Abou Khaled, Heiko Schuldt, Roland Schegg, Piotr S. Szczepaniak, Ahmed Serhrouchni, Florian Évéquoz and Francesco Carrino. Their work appears in journals such as Computers & Industrial Engineering, Journal of Ambient Intelligence and Humanized Computing and Journal of Electronic Science and Technology.

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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