Dan Lahav

590 total citations
12 papers, 166 citations indexed

About

Dan Lahav is a scholar working on Artificial Intelligence, Sociology and Political Science and Molecular Biology. According to data from OpenAlex, Dan Lahav has authored 12 papers receiving a total of 166 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 3 papers in Sociology and Political Science and 2 papers in Molecular Biology. Recurrent topics in Dan Lahav's work include Topic Modeling (6 papers), Misinformation and Its Impacts (3 papers) and Natural Language Processing Techniques (3 papers). Dan Lahav is often cited by papers focused on Topic Modeling (6 papers), Misinformation and Its Impacts (3 papers) and Natural Language Processing Techniques (3 papers). Dan Lahav collaborates with scholars based in Israel, United States and United Kingdom. Dan Lahav's co-authors include Noam Slonim, Shai Gretz, Assaf Toledo, Noam Shomron, Ahuva Weiss‐Meilik, Amos Adler, Yazeed Zoabi, Gillian Dank, Michal Jacovi and Eyal Ranen and has published in prestigious journals such as Scientific Reports, Journal of Medical Internet Research and The Veterinary Journal.

In The Last Decade

Dan Lahav

11 papers receiving 160 citations

Peers

Dan Lahav
Cynthia Gao United States
Galit Lukin United States
Harshad Hegde United States
Amanda Hicks United States
Shu Yang China
Cynthia Gao United States
Dan Lahav
Citations per year, relative to Dan Lahav Dan Lahav (= 1×) peers Cynthia Gao

Countries citing papers authored by Dan Lahav

Since Specialization
Citations

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

Fields of papers citing papers by Dan Lahav

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dan Lahav

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

All Works

12 of 12 papers shown
1.
Gretz, Shai, Assaf Toledo, Dan Lahav, et al.. (2023). Benchmark Data and Evaluation Framework for Intent Discovery Around COVID-19 Vaccine Hesitancy. 1358–1370. 1 indexed citations
2.
Nevo, Sella, et al.. (2023). Securing Artificial Intelligence Model Weights: Interim Report. RAND Corporation eBooks.
3.
Sedoc, João, Assaf Toledo, Shai Gretz, et al.. (2022). Chatbot-Delivered COVID-19 Vaccine Communication Message Preferences of Young Adults and Public Health Workers in Urban American Communities: Qualitative Study. Journal of Medical Internet Research. 24(7). e38418–e38418. 18 indexed citations
4.
Sedoc, João, Shai Gretz, Assaf Toledo, et al.. (2022). Usability and Credibility of a COVID-19 Vaccine Chatbot for Young Adults and Health Workers in the United States: Formative Mixed Methods Study. JMIR Human Factors. 10. e40533–e40533. 17 indexed citations
5.
Lahav, Dan, Bailey Kuehl, Sravanthi Parasa, et al.. (2022). A Search Engine for Discovery of Scientific Challenges and Directions. Proceedings of the AAAI Conference on Artificial Intelligence. 36(11). 11982–11990. 15 indexed citations
6.
Zoabi, Yazeed, et al.. (2021). Predicting bloodstream infection outcome using machine learning. Scientific Reports. 11(1). 20101–20101. 22 indexed citations
7.
Talmor, Alon, Dan Lahav, Yizhong Wang, et al.. (2021). MultiModalQA: Complex Question Answering over Text, Tables and Images. arXiv (Cornell University). 5 indexed citations
8.
Lahav, Dan, et al.. (2020). Interactive Extractive Search over Biomedical Corpora. 28–37. 12 indexed citations
9.
Toledo, Assaf, Shai Gretz, Dan Lahav, et al.. (2019). Automatic Argument Quality Assessment - New Datasets and Methods. 5624–5634. 25 indexed citations
10.
Bilu, Yonatan, Ariel Gera, Daniel Hershcovich, et al.. (2019). Argument Invention from First Principles. 1013–1026. 13 indexed citations
11.
Ranen, Eyal, et al.. (2007). Oesophageal sarcomas in dogs: Histological and clinical evaluation. The Veterinary Journal. 178(1). 78–84. 19 indexed citations
12.
Steinman, Amir, Caroline Banet-Noach, Lubov Simanov, et al.. (2006). Experimental Infection of Common Garter Snakes (Thamnophis sirtalis) with West Nile Virus. Vector-Borne and Zoonotic Diseases. 6(4). 361–368. 19 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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