Abstract
The amount of news content on the Web is increasing, enabling users to access news articles coming from a variety of sources: from newswires, news agencies, blogs, and at various places, e.g. even within Web search engines result pages. Anyhow, it still is a challenge for current search engines to decide which news events are worth being shown to the user (either for a newsworthy query or in a news portal). In this paper we define the task of predicting the future impact of news events. Being able to predict event impact will, for example, enable a newspaper to decide whether to follow a specific event or not, or a news search engine which stories to display. We define a flexible framework that, given some definition of impact, can predict its future development at the beginning of the event. We evaluate several possible definitions of event impact and experimentally identify the best features for each of them.
Keywords
- Aggregation Method
- News Article
- Event Impact
- Partial Event
- Future Impact
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, access via your institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Demartini, G., Siersdorfer, S.: Dear Search Engine: What’s your opinion about...? - Sentiment Analysis for Semantic Enrichment of Web Search Results. In: Semantic Search 2010 Workshop located at the 19th Int. WWW 2010 (2010)
Diaz, F.: Integration of news content into web results. In: WSDM 2009. ACM, New York (2009)
Finkel, J.R., Grenager, T., Manning, C.: Incorporating non-local information into information extraction systems by gibbs sampling. In: ACL 2005. Association for Computational Linguistics, Stroudsburg (2005)
Fisichella, M., Stewart, A., Denecke, K., Nejdl, W.: Unsupervised public health event detection for epidemic intelligence. In: CIKM 2010, New York, NY, USA (2010)
Galutung, J., Ruge, M.H.: The structure of foreign news. the presentation of the congo, cuba and cyprus crises in four foreign newspapers. Journal of Peace Research 2, 64–91 (1965)
Hall, M.: Correlation-based Feature Selection for Machine Learning (1998)
Hu, M., Sun, A., Lim, E.-P.: Event detection with common user interests. In: Proceeding of the 10th ACM Workshop on Web Information and Data Management, WIDM 2008. ACM, New York (2008)
Krestel, R., Mehta, B.: Predicting news story importance using language features. In: Web Intelligence, pp. 683–689. IEEE (2008)
Li, Z., Wang, B., Li, M., Ma, W.-Y.: A Probabilistic Model for Retrospective News Event Detection. In: SIGIR, pp. 106–113 (2005)
Lin, C.X., Zhao, B., Mei, Q., Han, J.: Pet: a statistical model for popular events tracking in social communities. In: KDD 2010. ACM, New York (2010)
Mizzaro, S.: Relevance: The whole history. JASIS 48(9), 810–832 (1997)
Patton, R.M., Potok, T.E.: Identifying event impacts by monitoring the news media. In: Information Visualisation, IV 2008 (July 2008)
Patton, R.M., Treadwell, J.N., Kerekes, R.A., Potok, T.E.: Discovery, analysis, and characteristics of event impacts. In: Information Fusion 2008 (June 2008)
San Pedro, J., Siersdorfer, S.: Ranking and classifying attractiveness of photos in folksonomies. In: WWW 2009. ACM, New York (2009)
Shevade, S.K., Keerthi, S.S., Bhattacharyya, C., Murthy, K.R.K.: Improvements to the smo algorithm for svm regression. IEEE Transactions on Neural Networks 11(5), 1188–1193 (2000)
Soboroff, I.: Overview of the trec 2004 novelty track. In: Voorhees, E.M., Buckland, L.P. (eds.) TREC, Special Publication 500-261. National Institute of Standards and Technology (NIST) (2004)
Soboroff, I., Harman, D.: Overview of the trec 2003 novelty track. In: TREC (2003)
Staab, J.F.: The role of news factors in news selection: A theoretical reconsideration. European Journal of Communication 5, 423–443 (1990)
Tsagkias, M., Weerkamp, W., de Rijke, M.: Predicting the volume of comments on online news stories. In: CIKM 2009. ACM, New York (2009)
Verhoeven, P.: Sound-bite science: On the brevity of science and scientific experts in western european television news. Science Communication 32(3), 330–335 (2010)
Zhang, K., Zi, J., Wu, L.G.: New event detection based on indexing-tree and named entity. In: SIGIR 2007. ACM, New York (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Gaugaz, J., Siehndel, P., Demartini, G., Iofciu, T., Georgescu, M., Henze, N. (2012). Predicting the Future Impact of News Events. In: Baeza-Yates, R., et al. Advances in Information Retrieval. ECIR 2012. Lecture Notes in Computer Science, vol 7224. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28997-2_5
Download citation
DOI: https://doi.org/10.1007/978-3-642-28997-2_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-28996-5
Online ISBN: 978-3-642-28997-2
eBook Packages: Computer ScienceComputer Science (R0)
