Automatic text processing: the transformation, analysis, and retrieval of information by computer
Automatic text processing: the transformation, analysis, and retrieval of information by computer
Subtopic structuring for full-length document access
SIGIR '93 Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval
Proceedings of the 20th annual international ACM SIGIR conference on Research and development in information retrieval
Learning dictionaries for information extraction by multi-level bootstrapping
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Linux Journal
Learning Subjective Adjectives from Corpora
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
TextTiling: segmenting text into multi-paragraph subtopic passages
Computational Linguistics
Predicting the semantic orientation of adjectives
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
PRINCIPAR: an efficient, broad-coverage, principle-based parser
COLING '94 Proceedings of the 15th conference on Computational linguistics - Volume 1
Automatically collecting, monitoring, and mining japanese weblogs
Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
Communications of the ACM - The Blogosphere
Communications of the ACM - The Blogosphere
Identifying opinionated sentences
NAACL-Demonstrations '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology: Demonstrations - Volume 4
Major topic detection and its application to opinion summarization
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Computational Linguistics
A bootstrapping method for learning semantic lexicons using extraction pattern contexts
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
Learning extraction patterns for subjective expressions
EMNLP '03 Proceedings of the 2003 conference on Empirical methods in natural language processing
EMNLP '03 Proceedings of the 2003 conference on Empirical methods in natural language processing
Understanding how bloggers feel: recognizing affect in blog posts
CHI '06 Extended Abstracts on Human Factors in Computing Systems
Sentiment retrieval using generative models
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
Feature subsumption for opinion analysis
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
| Hi-index | 0.00 |
Web logs (blogs) are a fast growing forum for people of all ages to express their feelings and opinions on topics of interest. The entries are often written in informal language without the structure found in newswire or published articles. One blog entry may contain many topics, these topics may express an opinion or a fact on a particular topic. This research is in contrast to work on opinion detection which has been carried out on more formally authored texts and on segments that are either whole documents or sentences. Whole web logs are divided into topics using a simple text segmentation approach. Similarity scores are used to distinguish where topic changes occur. The results are compared to human-evaluated topic changes and the most accurate algorithm is used in the remainder of the research. Words within each topic-block are allocated weightings depending on their opinion-bearing strength. Two approaches of using these weights, the sum and the maximum, are used to determine whether the topic-block is opinion-bearing or non-opinion-bearing. The opinion-bearing topic-blocks are rated by human evaluators as either opinion-bearing or non-opinion-bearing with precision of 67% for approach A and 70% for approach B. These results are compared with two approaches on published text to identify the difference between web logs and published articles.