Association for Computational Linguistics
- Research works
- 119 ▼ 87% vs 2013–17
- Citations
- 1.7k 14.4 per fractional work
- Top-10% rate
- 8.0% record average 16.5%
- Open access
- 51% world 28%
Not ranked overall: Association for Computational Linguistics is under the volume floor below which an excellence rate is noise. Not ranked is not the same as ranked last.
Field profile
Location quotient across every field it publishes in: outside the ring is more than an institution of this size would be expected to publish, inside it is less.
Rings at 0.5×, 1× and 2×. Widest outward: Computer Science, 6.9×. Every wedge is a field page.
Which keywords describe research at Association for Computational Linguistics?
By fractional works in 2022–2025, weighted toward what it does more of than the world: Corpus Linguistics, Neural Machine Translation, Statistical Machine Translation, Neural Networks, Text Classification, Machine Translation, Machine Learning and Topic Modeling.
- Self-Organizing Maps
- Innovation
- Film Industry
- Box Office
- Semantic Web
- Data Integration
- Word Representation
- Deep Learning
- Natural Language Processing
- Machine Translation
- Neural Networks
- Neural Machine Translation
- Corpus Linguistics
- Statistical Machine Translation
- Machine Learning
- Text Classification
- Topic Modeling
- Semantic Similarity
- Big Data
- Knowledge Representation
- Backpropagation Learning
- Creativity
- Healthcare Policy
- Public Health
Size is fractional works in 2022–2025 in the topics tagged with each word; colour is the word's share of this institution's work against its share of the world's. The 24 words are chosen for being large and distinctive. Each links to the topic it comes from most.
All 24 words, with their numbers
- Corpus Linguistics6▲ 121×2 topics
- Neural Machine Translation5▲ 250×1 topic
- Statistical Machine Translation5▲ 250×1 topic
- Neural Networks3▲ 9.7×3 topics
- Machine Learning3▲ 3.7×6 topics
- Machine Translation2▲ 58×2 topics
- Text Classification2▲ 63×2 topics
- Natural Language Processing2▲ 35×4 topics
- Topic Modeling2▲ 57×2 topics
- Deep Learning2▲ 2.4×4 topics
- Semantic Similarity2▲ 63×1 topic
- Word Representation2▲ 63×1 topic
- Big Data1▲ 6.0×3 topics
- Data Integration1▲ 30×2 topics
- Knowledge Representation1▲ 56×3 topics
- Semantic Web1▲ 53×2 topics
- Backpropagation Learning1▲ 58×1 topic
- Box Office1▲ 179×1 topic
- Creativity1▲ 78×1 topic
- Film Industry1▲ 179×1 topic
- Healthcare Policy1▲ 49×1 topic
- Innovation1▲ 4.5×1 topic
- Public Health1▲ 3.2×1 topic
- Self-Organizing Maps1▲ 58×1 topic
Which research topics does Association for Computational Linguistics publish most on?
By volume in 2022–2025: Natural Language Processing Techniques, Topic Modeling, Creativity in Education and Neuroscience and Cinema and Media Studies.
Area is fractional works; colour is the subfield each topic belongs to.
- 1 Natural Language Processing Techniques Artificial Intelligence 5 works
- 2 Topic Modeling Artificial Intelligence 2 works
- 3 Creativity in Education and Neuroscience Experimental and Cognitive Psychology 1 works
- 4 Cinema and Media Studies Economics and Econometrics 1 works
- 5 Healthcare Systems and Practices General Health Professions 1 works
- 6 Neural Networks and Applications Artificial Intelligence 1 works
- 7 Semantic Web and Ontologies Artificial Intelligence 1 works
- 8 Artificial Intelligence in Law Political Science and International Relations 1 works
- 9 Text Readability and Simplification Artificial Intelligence 1 works
- 10 Wikis in Education and Collaboration Communication 0 works
How open and international is its research?
Against the world’s own shares — the tick on each track. Both are shares of its output, so they sit on one scale and can be read against each other as well as against the world.
World: 28% of research is openly available.
World: 19% is written across borders.
How has Association for Computational Linguistics's research output changed?
Output in 2018–2022 was 87% lower than in 2013–2017.
The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.
Research measures only: rankings here say nothing about teaching, admissions or student experience. Comparable institutions and collaboration partners are in the interactive view on the map.