Daniel Mican

30 papers receiving 321 citations

Peers

Daniel Mican
Comparison fields: 5 of 65
  • Information Systems and Management 109
  • Health Informatics 10
  • Management Information Systems 46
  • Marketing 43
  • Computer Science Applications 22
Replace Ahmet Ayaz with:
Ahmet Ayaz Türkiye
Kovila Coopamootoo United Kingdom
N. D. Oye Nigeria
Alexander Pelaez United States
Lea Reis Germany
Konstantinos C. Giotopoulos Greece
Penny Duquenoy United Kingdom
Emmanuel Awuni Kolog Ghana
Farkhondeh Hassandoust New Zealand
Norhisham Mohamad-Nordin Malaysia
Daniel Mican relative to Ahmet Ayaz Türkiye Ahmet Ayaz's profile →
Citations per field
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Ahmet Ayaz · 1×
Citations per year

Countries citing papers authored by Daniel Mican

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Mican

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 10 scholars most cited alongside Daniel Mican, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Daniel Mican Line = papers co-authored together Daniel Mican links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202188
2 202051
3 201021
4 202118
5 202014
6 202214
7 201114
8 202413
9 202312
10 202111
11 201211
12 202010
13 20198
14
Preprocessing and Content/Navigational Pages Identification as Premises for an Extended Web Usage Mining Model Development
20097
15 20107
16 20256
17 20206
18
Web Content Management Systems, a Collaborative Environment in the Information Society
20095
19 20104
20 20233

About Daniel Mican

Daniel Mican is a scholar working on Sociology and Political Science, Information Systems, Information Systems and Management, Artificial Intelligence and Computer Networks and Communications, having authored 32 papers that have together received 340 indexed citations. Recurring topics across this work include Digital Marketing and Social Media (9 papers), Technology Adoption and User Behaviour (8 papers), Recommender Systems and Techniques (6 papers), Business Process Modeling and Analysis (5 papers), Impact of Technology on Adolescents (4 papers), Semantic Web and Ontologies (4 papers), Peer-to-Peer Network Technologies (3 papers) and Misinformation and Its Impacts (3 papers). The work is most often cited by research in Information Systems and Management (109 citations), Health Informatics (10 citations), Management Information Systems (46 citations), Marketing (43 citations) and Computer Science Applications (22 citations). Daniel Mican has collaborated with scholars based in Romania, Germany and Netherlands. Frequent co-authors include Dan‐Andrei Sitar‐Tăut, Ovidiu Ioan Moisescu, Lena Frömbling, Marko Sarstedt, Robert Andrei Buchmann, Irene Vanderfeesten, Codruța Mare, Raluca Bunduchi, Adela Sitar-Tăut and Bogdan Cramariuc. Their work appears in journals such as Technological Forecasting and Social Change, Online Information Review, Expert Systems with Applications, Social Science Computer Review and Kybernetes.

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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