Data Technologies and Applications

230 papers and 1.4k indexed citations i.

About

The 230 papers published in Data Technologies and Applications in the last decades have received a total of 1.4k indexed citations. Papers published in Data Technologies and Applications usually cover Artificial Intelligence (94 papers), Information Systems (62 papers) and Sociology and Political Science (42 papers) specifically the topics of Digital Marketing and Social Media (28 papers), Technology Adoption and User Behaviour (20 papers) and Topic Modeling (20 papers). The most active scholars publishing in Data Technologies and Applications are Tao Zhou, Zheshi Bao, Enayat Rajabi, Yun Zhu, Donghong Ding, Julian Risch, Saeed Siyal, Ralf Krestel, Emmanouel Garoufallou and Sirje Virkus.

In The Last Decade

Fields of papers published in Data Technologies and Applications

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Data Technologies and Applications. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in Data Technologies and Applications.

Countries where authors publish in Data Technologies and Applications

Since Specialization
Citations

This map shows the geographic impact of research published in Data Technologies and Applications. 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 papers published in Data Technologies and Applications with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Data Technologies and Applications more than expected).

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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2025