Ariel Gera

33 total papers · 537 total citations
12 papers, 152 citations indexed

About

Ariel Gera is a scholar working on Artificial Intelligence, Information Systems and Language and Linguistics. According to data from OpenAlex, Ariel Gera has authored 12 papers receiving a total of 152 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Artificial Intelligence, 1 paper in Information Systems and 1 paper in Language and Linguistics. Recurrent topics in Ariel Gera's work include Topic Modeling (9 papers), Natural Language Processing Techniques (9 papers) and Advanced Text Analysis Techniques (4 papers). Ariel Gera is often cited by papers focused on Topic Modeling (9 papers), Natural Language Processing Techniques (9 papers) and Advanced Text Analysis Techniques (4 papers). Ariel Gera collaborates with scholars based in United States and Israel. Ariel Gera's co-authors include Noam Slonim, Alon Halfon, Liat Ein‐Dor, Eyal Shnarch, Lena Dankin, Ranit Aharonov, Yoav Katz, Leshem Choshen, Marina Danilevsky and Yonatan Bilu and has published in prestigious journals such as Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers).

In The Last Decade

Ariel Gera

8 papers receiving 142 citations

Author Peers

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

Author						Papers	Cites
Ariel Gera	125	25	9	9	6	12	152
Alon Halfon	138 1.1×	22 0.9×	12 1.3×	10 1.1×	8 1.3×	11	166
Vipula Rawte	78 0.6×	14 0.6×	4 0.4×	9 1.0×	5 0.8×	12	123
Heather Holmback	106 0.8×	41 1.6×	9 1.0×	8 0.9×	5 0.8×	15	158
Yuri Kuratov	127 1.0×	21 0.8×	9 1.0×	8 0.9×	17 2.8×	13	158
Tanya Korelsky	228 1.8×	33 1.3×	8 0.9×	6 0.7×	9 1.5×	13	250
Shuofei Qiao	141 1.1×	26 1.0×	24 2.7×	21 2.3×	7 1.2×	12	185
Potsawee Manakul	129 1.0×	17 0.7×	8 0.9×	5 0.6×	4 0.7×	13	166
Ioana Hulpuş	141 1.1×	48 1.9×	14 1.6×	8 0.9×	6 1.0×	18	186
Alexey Sorokin	160 1.3×	20 0.8×	17 1.9×	6 0.7×	13 2.2×	16	184
Arle Lommel	204 1.6×	27 1.1×	19 2.1×	5 0.6×	4 0.7×	23	276

Countries citing papers authored by Ariel Gera

Since Specialization

Citations

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

Fields of papers citing papers by Ariel Gera

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ariel Gera

This figure shows the co-authorship network connecting the top 25 collaborators of Ariel Gera. A scholar is included among the top collaborators of Ariel Gera 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 Ariel Gera. Ariel Gera 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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