Patterns of search: analyzing and modeling Web query refinement
UM '99 Proceedings of the seventh international conference on User modeling
Analysis of a very large web search engine query log
ACM SIGIR Forum
Real life, real users, and real needs: a study and analysis of user queries on the web
Information Processing and Management: an International Journal
Bursty and Hierarchical Structure in Streams
Data Mining and Knowledge Discovery
Identifying similarities, periodicities and bursts for online search queries
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Hourly analysis of a very large topically categorized web query log
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
On the Bursty Evolution of Blogspace
World Wide Web
Semantic similarity between search engine queries using temporal correlation
WWW '05 Proceedings of the 14th international conference on World Wide Web
Query chains: learning to rank from implicit feedback
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Parameter free bursty events detection in text streams
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Time-dependent semantic similarity measure of queries using historical click-through data
Proceedings of the 15th international conference on World Wide Web
Topics over time: a non-Markov continuous-time model of topical trends
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Event detection from evolution of click-through data
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Temporal analysis of a very large topically categorized Web query log
Journal of the American Society for Information Science and Technology
Why we search: visualizing and predicting user behavior
Proceedings of the 16th international conference on World Wide Web
Causal relation of queries from temporal logs
Proceedings of the 16th international conference on World Wide Web
Heads and tails: studies of web search with common and rare queries
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Entropy of search logs: how hard is search? with personalization? with backoff?
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
An experimental comparison of click position-bias models
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
Using subspace analysis for event detection from web click-through data
Proceedings of the 17th international conference on World Wide Web
Learning about the world through long-term query logs
ACM Transactions on the Web (TWEB)
Understanding the relationship between searchers' queries and information goals
Proceedings of the 17th ACM conference on Information and knowledge management
The query-flow graph: model and applications
Proceedings of the 17th ACM conference on Information and knowledge management
Beyond the session timeout: automatic hierarchical segmentation of search topics in query logs
Proceedings of the 17th ACM conference on Information and knowledge management
Meme-tracking and the dynamics of the news cycle
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Discovery of interactive graphs for understanding and searching time-indexed corpora
Knowledge and Information Systems
The Effects of Query Bursts on Web Search
WI-IAT '10 Proceedings of the 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
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The Internet has become for many the most important medium for staying informed about current news events. Some events cause heightened interest on a topic, which in turn yields a higher frequency of the search queries related to it. These queries are going through a “query burst”. In this paper we examine the behavior of search engine users during a query burst, compared to before and after the burst. We are interested in how this behavior changes, and how it affects other stake-holders in web search.We analyze one year of web-search and news-search logs, looking at query bursts from multiple perspectives. First, we adopt the perspective of search engine users, describing changes in their effort and interest while searching. Second, we adopt the perspective of news providers by comparing web search and news search query bursts. Third, we look at the burst from the perspective of content providers.We study the conditions under which content providers can “ride” a wave of increased interest on a topic, and obtain a share of the user's increased attention. We do so by identifying the class of queries that can be considered as an opportunity for content providers that are “late-comers” for a query, in the sense of not being among the first to write about its topic. We also present a simple model for predicting the click share content providers could obtain if they decide to provide content about these queries.