%0 Conference Paper %1 jurczyk2007discovering %A Jurczyk, Pawel %A Agichtein, Eugene %B Proceedings of the sixteenth ACM conference on Conference on information and knowledge management %C New York, NY, USA %D 2007 %I ACM %K answering collaborative quality question reputation search social web alexandria %P 919--922 %R 10.1145/1321440.1321575 %T Discovering authorities in question answer communities by using link analysis %U http://doi.acm.org/10.1145/1321440.1321575 %X Question-Answer portals such as Naver and Yahoo! Answers are quickly becoming rich sources of knowledge on many topics which are not well served by general web search engines. Unfortunately, the quality of the submitted answers is uneven, ranging from excellent detailed answers to snappy and insulting remarks or even advertisements for commercial content. Furthermore, user feedback for many topics is sparse, and can be insufficient to reliably identify good answers from the bad ones. Hence, estimating the authority of users is a crucial task for this emerging domain, with potential applications to answer ranking, spam detection, and incentive mechanism design. We present an analysis of the link structure of a general-purpose question answering community to discover authoritative users, and promising experimental results over a dataset of more than 3 million answers from a popular community QA site. We also describe structural differences between question topics that correlate with the success of link analysis for authority discovery. %@ 978-1-59593-803-9

@inproceedings{jurczyk2007discovering, abstract = {Question-Answer portals such as Naver and Yahoo! Answers are quickly becoming rich sources of knowledge on many topics which are not well served by general web search engines. Unfortunately, the quality of the submitted answers is uneven, ranging from excellent detailed answers to snappy and insulting remarks or even advertisements for commercial content. Furthermore, user feedback for many topics is sparse, and can be insufficient to reliably identify good answers from the bad ones. Hence, estimating the authority of users is a crucial task for this emerging domain, with potential applications to answer ranking, spam detection, and incentive mechanism design. We present an analysis of the link structure of a general-purpose question answering community to discover authoritative users, and promising experimental results over a dataset of more than 3 million answers from a popular community QA site. We also describe structural differences between question topics that correlate with the success of link analysis for authority discovery.}, acmid = {1321575}, added-at = {2012-10-11T17:43:00.000+0200}, address = {New York, NY, USA}, author = {Jurczyk, Pawel and Agichtein, Eugene}, biburl = {https://www.bibsonomy.org/bibtex/235394620d2654db8543d5da60f6f00dc/jaeschke}, booktitle = {Proceedings of the sixteenth ACM conference on Conference on information and knowledge management}, doi = {10.1145/1321440.1321575}, interhash = {1c2953be3517384681b6ac831da2c766}, intrahash = {35394620d2654db8543d5da60f6f00dc}, isbn = {978-1-59593-803-9}, keywords = {answering collaborative quality question reputation search social web alexandria}, location = {Lisbon, Portugal}, numpages = {4}, pages = {919--922}, publisher = {ACM}, timestamp = {2014-07-28T15:57:31.000+0200}, title = {Discovering authorities in question answer communities by using link analysis}, url = {http://doi.acm.org/10.1145/1321440.1321575}, year = 2007 }