Sonal Garg

489 total citations
13 papers, 292 citations indexed

About

Sonal Garg is a scholar working on Information Systems, Sociology and Political Science and Artificial Intelligence. According to data from OpenAlex, Sonal Garg has authored 13 papers receiving a total of 292 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Information Systems, 10 papers in Sociology and Political Science and 7 papers in Artificial Intelligence. Recurrent topics in Sonal Garg's work include Spam and Phishing Detection (10 papers), Misinformation and Its Impacts (10 papers) and Advanced Malware Detection Techniques (5 papers). Sonal Garg is often cited by papers focused on Spam and Phishing Detection (10 papers), Misinformation and Its Impacts (10 papers) and Advanced Malware Detection Techniques (5 papers). Sonal Garg collaborates with scholars based in India. Sonal Garg's co-authors include Dilip Kumar Sharma, Namita Mittal, Basant Agarwal and Rajesh Katoch and has published in prestigious journals such as Computers & Industrial Engineering, Computational Intelligence and Neuroscience and Tropical Animal Health and Production.

In The Last Decade

Sonal Garg

12 papers receiving 280 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Sonal Garg India	8	189	150	150	55	15	13	292
Peter Snyder United States	9	119 0.6×	78 0.5×	138 0.9×	74 1.3×	8 0.5×	20	213
Ambreen Nazir China	10	323 1.7×	172 1.1×	121 0.8×	17 0.3×	18 1.2×	12	412
Michael Brennan United States	5	291 1.5×	149 1.0×	211 1.4×	56 1.0×	17 1.1×	8	376
Renato M. Silva Brazil	8	176 0.9×	134 0.9×	193 1.3×	46 0.8×	12 0.8×	24	290
Youness Madani Morocco	11	190 1.0×	60 0.4×	134 0.9×	13 0.2×	13 0.9×	23	275
Ahmed Abbasi Pakistan	7	129 0.7×	41 0.3×	47 0.3×	33 0.6×	42 2.8×	9	215
Konstantin Bauman United States	6	150 0.8×	40 0.3×	153 1.0×	12 0.2×	21 1.4×	18	229
Liliana Chanona-Hernández Mexico	6	199 1.1×	29 0.2×	73 0.5×	17 0.3×	11 0.7×	17	276
Hadeer Ahmed Canada	4	168 0.9×	230 1.5×	238 1.6×	85 1.5×	6 0.4×	5	314
Toshikazu Fukushima Japan	6	315 1.7×	55 0.4×	121 0.8×	18 0.3×	25 1.7×	16	362

Countries citing papers authored by Sonal Garg

Since Specialization

Citations

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

Fields of papers citing papers by Sonal Garg

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sonal Garg

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

All Works

Sort: Min cites: Since: Top N: Style:

13 of 13 papers shown

1.

Garg, Sonal & Dilip Kumar Sharma. (2024). Fake news detection in the Hindi language using multi‐modality via transfer and ensemble learning. Internet Technology Letters. 8(1). 1 indexed citations

2.

Sharma, Dilip Kumar, et al.. (2022). Utilizing Word Embedding and Linguistic Features for Fake News Detection. 844–848. 5 indexed citations

3.

Garg, Sonal & Dilip Kumar Sharma. (2022). Linguistic features based framework for automatic fake news detection. Computers & Industrial Engineering. 172. 108432–108432. 40 indexed citations

4.

Garg, Sonal & Dilip Kumar Sharma. (2022). Role of ELMo Embedding in Detecting Fake News on Social Media. 57–60. 3 indexed citations

5.

Garg, Sonal & Dilip Kumar Sharma. (2022). Fake News Classification via CNN. 61–63.

6.

Sharma, Dilip Kumar & Sonal Garg. (2021). IFND: a benchmark dataset for fake news detection. Complex & Intelligent Systems. 9(3). 2843–2863. 46 indexed citations

7.

Sharma, Dilip Kumar, et al.. (2021). Evaluation of Tools and Extension for Fake News Detection. 227–232. 16 indexed citations

8.

Sharma, Dilip Kumar & Sonal Garg. (2021). Machine Learning Methods to identify Hindi Fake News within social-media. 1–6. 10 indexed citations

9.

Garg, Sonal & Dilip Kumar Sharma. (2020). Phony News Detection using Machine Learning and Deep-Learning Techniques. 27–32. 12 indexed citations

10.

Garg, Sonal & Dilip Kumar Sharma. (2020). New Politifact: A Dataset for Counterfeit News. 17–22. 16 indexed citations

11.

Garg, Sonal & Dilip Kumar Sharma. (2015). Feature based clustering considering context dependent words. 713–718. 4 indexed citations

12.

Agarwal, Basant, et al.. (2015). Sentiment Analysis Using Common-Sense and Context Information. Computational Intelligence and Neuroscience. 2015. 1–9. 132 indexed citations

13.

Garg, Sonal, et al.. (1998). Efficacy of Flumethrin Pour-On Against Damalinia caprae of Goats (Capra hircus). Tropical Animal Health and Production. 30(5). 273–278. 7 indexed citations

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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