Citation Context and Sentiment Analysis
Citation context and sentiment analysis is the scientometric text-mining technique that reads the words around a citation to recover why one paper cites another and with what attitude. Standard citation counting treats every citation as an equal, polarity-free vote, but Simone Teufel, Advaith Siddharthan and Dan Tidhar's 2006 EMNLP work showed that citations serve distinct rhetorical functions — using a method, contrasting with prior work, acknowledging a basis, or merely referencing in passing — and that these functions can be classified automatically from the citing sentence. Awais Athar's 2011 work extended this to sentiment, distinguishing positive, neutral, and negative (critical) citations using sentence-structure features. Together these methods turn the raw citation graph into a typed, sentiment-bearing graph, enabling more meaningful impact measures, better citation indexers, and summaries of how a paper has been received.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
- Teufel, S., Siddharthan, A., & Tidhar, D. (2006). Automatic classification of citation function. In Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing (EMNLP 2006), 103-110. · URL
- Athar, A. (2011). Sentiment analysis of citations using sentence structure-based features. In Proceedings of the ACL 2011 Student Session, 81-87. · URL
精选声明
声明已持久化到证据分类账中，每个声明都有自己的评估。
当分类账中没有声明时，此视图不会自行创建声明评估。
相关方法
从方法图中生成，显示为机器建议的关系 — 不推断任何证据声明。