Adam Bermingham
Artificial Intelligence · 2010–2011
A researcher in the Science corpus: 2 papers; trusts 15 researchers and is trusted by 10 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 13 citations into it; #14,520 of 35,345 by trust here, #24,417 by citations
Whom Adam Bermingham trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Nicholas A. Diakopoulos
- David A. Shamma
- Yoav Freund
- Bo Pang
- Andrea Esuli
- Sitaram Asur
- Andrew F. Hayes
- Johan Bollen
- Robert E. Schapire
- Lillian Lee
Who trusts Adam Bermingham overall
- Manoochehr Ghiassi
- Kun Liu
- Wafa S. Alorainy
- Saif M. Mohammad
- J. Skinner
- Matthew S. Gerber
- Wu-Jun Li
- Daniel Gayo-Avello
- P. Burnap
- David Zimbra
Papers from Adam Bermingham's perspective
Ordered by how strongly the researchers Adam Bermingham trusts endorse each paper. Same corpus, a different order for every researcher.
- A Sentimental Education: Sentiment Analysis Using Subjectivity Summarization Based on Minimum Cuts
- Recognizing Contextual Polarity in Phrase-Level Sentiment Analysis
- SENTIWORDNET: A Publicly Available Lexical Resource for Opinion Mining (International Conference on Language Resources and Evaluation)
- Sentiment classification on customer feedback data: noisy data, large feature vectors, and the role of linguistic analysis (International Conference on Computational Linguistics)
- Predicting the Future with Social Media
- Twitter mood predicts the stock market
- From Tweets to Polls: Linking Text Sentiment to Public Opinion Time Series (International Conference on Web and Social Media)
- Procedia Social and Behavioral Sciences
- Sentiment Classification Using Word Sub-sequences and Dependency Sub-trees
- Attention is All you Need (Neural Information Processing Systems)
Their papers
- On Using Twitter to Monitor Political Sentiment and Predict Election Results (2011) — 433 citations
- Classifying sentiment in microblogs: is brevity an advantage? (2010) — 392 citations