Noura Farra

2.2k total citations · 2 hit papers
15 papers, 1.3k citations indexed

About

Noura Farra is a scholar working on Artificial Intelligence, Social Psychology and Computer Vision and Pattern Recognition. According to data from OpenAlex, Noura Farra has authored 15 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 3 papers in Social Psychology and 3 papers in Computer Vision and Pattern Recognition. Recurrent topics in Noura Farra's work include Topic Modeling (10 papers), Sentiment Analysis and Opinion Mining (7 papers) and Advanced Text Analysis Techniques (6 papers). Noura Farra is often cited by papers focused on Topic Modeling (10 papers), Sentiment Analysis and Opinion Mining (7 papers) and Advanced Text Analysis Techniques (6 papers). Noura Farra collaborates with scholars based in United States, Lebanon and Qatar. Noura Farra's co-authors include Sara Rosenthal, Preslav Nakov, Ritesh Kumar, Shervin Malmasi, Marcos Zampieri, Hazem Hajj, Rawad Abou Assi, Nizar Habash, Kathy McKeown and Jill Burstein and has published in prestigious journals such as Machine Translation, Journal of Medical Imaging and Health Informatics and Figshare.

In The Last Decade

Noura Farra

15 papers receiving 1.2k citations

Hit Papers

SemEval-2017 Task 4: Sentiment Analysis in Twitter 2017 2026 2020 2023 2017 2019 100 200 300 400 500

Peers

Noura Farra
Noura Farra
Citations per year, relative to Noura Farra Noura Farra (= 1×) peers Muhammad Abdul-Mageed

Countries citing papers authored by Noura Farra

Since Specialization
Citations

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

Fields of papers citing papers by Noura Farra

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Noura Farra

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

All Works

15 of 15 papers shown
1.
Zampieri, Marcos, Shervin Malmasi, Preslav Nakov, et al.. (2019). SemEval-2019 Task 6: Identifying and Categorizing Offensive Language in Social Media (OffensEval). 75–86. 447 indexed citations breakdown →
2.
Farra, Noura. (2019). Cross-Lingual and Low-Resource Sentiment Analysis. Columbia Academic Commons (Columbia University). 3 indexed citations
3.
Zaghouani, Wajdi, Behrang Mohit, Nizar Habash, et al.. (2018). Large Scale Arabic Error Annotation: Guidelines and Framework. Figshare. 2362–2369. 32 indexed citations
4.
Rosenthal, Sara, Noura Farra, & Preslav Nakov. (2017). SemEval-2017 Task 4: Sentiment Analysis in Twitter. 502–518. 535 indexed citations breakdown →
5.
Rasooli, Mohammad Sadegh, Noura Farra, Axinia Radeva, Tao Yu, & Kathleen McKeown. (2017). Cross-lingual sentiment transfer with limited resources. Machine Translation. 32(1-2). 143–165. 22 indexed citations
6.
Farra, Noura & Kathy McKeown. (2017). SMARTies: Sentiment Models for Arabic Target entities. 1002–1013. 12 indexed citations
7.
Farra, Noura, Kathy McKeown, & Nizar Habash. (2015). Annotating Targets of Opinions in Arabic using Crowdsourcing. 89–98. 21 indexed citations
8.
Farra, Noura, Swapna Somasundaran, & Jill Burstein. (2015). Scoring Persuasive Essays Using Opinions and their Targets. 64–74. 34 indexed citations
9.
Farra, Noura, Nadi Tomeh, Alla Rozovskaya, & Nizar Habash. (2014). Generalized Character-Level Spelling Error Correction. 12 indexed citations
10.
Rozovskaya, Alla, Nizar Habash, Ramy Eskander, Noura Farra, & Wael Salloum. (2014). The Columbia System in the QALB-2014 Shared Task on Arabic Error Correction. 160–164. 12 indexed citations
11.
Tomeh, Nadi, Nizar Habash, Ryan M. Roth, et al.. (2013). Reranking with Linguistic and Semantic Features for Arabic Optical Character Recognition. Meeting of the Association for Computational Linguistics. 549–555. 6 indexed citations
12.
Farra, Noura, et al.. (2011). A novel mobile wireless sensing system for realtime monitoring of posture and spine stress. 428–431. 21 indexed citations
13.
Farra, Noura, Giuseppe Maria Raffa, Lama Nachman, & Hazem Hajj. (2011). Energy-efficient mobile gesture recognition with computation offloading. 1–6. 2 indexed citations
14.
Farra, Noura, et al.. (2011). A Mobile Sensing and Imaging System for Real-Time Monitoring of Spine Health. Journal of Medical Imaging and Health Informatics. 1(3). 238–245. 12 indexed citations
15.
Farra, Noura, et al.. (2010). Sentence-Level and Document-Level Sentiment Mining for Arabic Texts. 1114–1119. 130 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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