# NLPExplorer: Exploring the Universe of NLP Papers

arXiv: https://arxiv.org/abs/1910.07351 · HTML: https://mlsanity.com/paper/1910.07351/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 Oct 2019.

## Built on by (most cited first, 8 of 8)

- [D3: A Massive Dataset of Scholarly Metadata for Analyzing the State of Computer Science Research](https://mlsanity.com/paper/2204.13384/) (2022)
- [Exploring the Landscape of Natural Language Processing Research](https://mlsanity.com/paper/2307.10652/) (2023)
- [CS-Insights: A System for Analyzing Computer Science Research](https://mlsanity.com/paper/2210.06878/) (2022)
- [NLP-KG: A System for Exploratory Search of Scientific Literature in Natural Language Processing](https://mlsanity.com/paper/2406.15294/) (2024)
- [Revealing the Technology Development of Natural Language Processing: A Scientific Entity-Centric Perspective](https://mlsanity.com/paper/2606.29836/) (2026)
- [TweeNLP: A Twitter Exploration Portal for Natural Language Processing](https://mlsanity.com/paper/2106.10512/) (2021)
- [ACL-Verbatim: hallucination-free question answering for research](https://mlsanity.com/paper/2605.21102/) (2026)
- [CLICKER: A Computational LInguistics Classification Scheme for Educational Resources](https://mlsanity.com/paper/2112.08578/) (2021)

## Abstract (arXiv)

Understanding the current research trends, problems, and their innovative solutions remains a bottleneck due to the ever-increasing volume of scientific articles. In this paper, we propose NLPExplorer, a completely automatic portal for indexing, searching, and visualizing Natural Language Processing (NLP) research volume. NLPExplorer presents interesting insights from papers, authors, venues, and topics. In contrast to previous topic modelling based approaches, we manually curate five course-grained non-exclusive topical categories namely Linguistic Target (Syntax, Discourse, etc.), Tasks (Tagging, Summarization, etc.), Approaches (unsupervised, supervised, etc.), Languages (English, Chinese,etc.) and Dataset types (news, clinical notes, etc.). Some of the novel features include a list of young popular authors, popular URLs, and datasets, a list of topically diverse papers and recent popular papers. Also, it provides temporal statistics such as yearwise popularity of topics, datasets, and seminal papers. To facilitate future research and system development, we make all the processed datasets accessible through API calls. The current system is available at http://lingo.iitgn.ac.in:5001/