Ashima Yadav

47 total papers · 1.8k total citations
27 papers, 1.1k citations indexed

About

Ashima Yadav is a scholar working on Artificial Intelligence, Sociology and Political Science and Information Systems. According to data from OpenAlex, Ashima Yadav has authored 27 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Artificial Intelligence, 12 papers in Sociology and Political Science and 10 papers in Information Systems. Recurrent topics in Ashima Yadav's work include Misinformation and Its Impacts (12 papers), Sentiment Analysis and Opinion Mining (10 papers) and Spam and Phishing Detection (10 papers). Ashima Yadav is often cited by papers focused on Misinformation and Its Impacts (12 papers), Sentiment Analysis and Opinion Mining (10 papers) and Spam and Phishing Detection (10 papers). Ashima Yadav collaborates with scholars based in India, United States and France. Ashima Yadav's co-authors include Dinesh Kumar Vishwakarma, Ishita Gupta, Harshwardhan Khandait, Dinesh Kumar Vishwakarma, Ayush Agarwal, Rahul Katarya, Kuldeep Singh, Priyanka Meel, Akansha Singh and Krishna Kant Singh and has published in prestigious journals such as Sensors, Applied Soft Computing and Artificial Intelligence Review.

In The Last Decade

Ashima Yadav

26 papers receiving 1.1k citations

Hit Papers

Sentiment analysis using ... 2019 2026 2021 2023 2019 100 200 300 400 500

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Ashima Yadav 672 228 207 128 95 27 1.1k
Mohammed Ali Al-Garadi 737 1.1× 165 0.7× 152 0.7× 202 1.6× 50 0.5× 45 1.4k
Jürgen Lerner 222 0.3× 114 0.5× 366 1.8× 68 0.5× 56 0.6× 43 1.2k
Alessio Signorini 328 0.5× 273 1.2× 392 1.9× 44 0.3× 30 0.3× 12 1.4k
Jalal S. Alowibdi 362 0.5× 221 1.0× 206 1.0× 40 0.3× 21 0.2× 39 1.4k
Katarzyna Musiał 725 1.1× 235 1.0× 136 0.7× 157 1.2× 47 0.5× 81 1.4k
Matloob Khushi 725 1.1× 138 0.6× 180 0.9× 77 0.6× 44 0.5× 56 1.5k
Adam Sadilek 333 0.5× 120 0.5× 148 0.7× 101 0.8× 16 0.2× 31 1.4k
Aditya Joshi 1.0k 1.6× 170 0.7× 115 0.6× 66 0.5× 91 1.0× 69 1.3k
Ramakanth Kavuluru 801 1.2× 102 0.4× 83 0.4× 54 0.4× 62 0.7× 72 1.4k
Muhammad Shahzad Younis 311 0.5× 107 0.5× 56 0.3× 85 0.7× 106 1.1× 46 1.1k

Countries citing papers authored by Ashima Yadav

Since Specialization
Citations

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

Fields of papers citing papers by Ashima Yadav

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ashima Yadav

This figure shows the co-authorship network connecting the top 25 collaborators of Ashima Yadav. A scholar is included among the top collaborators of Ashima Yadav 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 Ashima Yadav. Ashima Yadav is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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