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What's on the grapevine?

Published: 29 June 2009 Publication History

Abstract

User generated content and social media (in the form of blogs, wikis, online video, microblogs, etc) are proliferating online. Grapevine conducts large scale data analysis on the social media collective, distilling and extracting information in real time. It aims to track entities and stories of interest in millions of blog posts, thousands of tweets, news items, etc., daily. Grapevine facilitates the interactive exploration of content, allowing users to discover interesting or surprising stories, optionally narrowed down on a specific demographic of interest (e.g. "What are Torontonians talking about on blogs?", "What are popular stories across news sources in Canada?", "What are financiers in Texas blogging about today?"). Stories of interest can be explored in a variety of ways, such as modifying their scope, obtaining related content (blog posts, news, etc), and examining their temporal evolution.

References

[1]
Wikipedia. http://www.wikipedia.org.
[2]
M. Banko, M. J. Cafarella, S. Soderland, M. Broadhead, and O. Etzioni. Open Information Extraction from the Web. In IJCAI, 2007.
[3]
N. Bansal and N. Koudas. BlogScope: A System for Online Analysis of High Volume Text Streams. In VLDB, 2007.
[4]
K. Bollacker, C. Evans, P. Paritosh, T. Sturge, and J. Taylor. Freebase: a collaboratively created graph database for structuring human knowledge. In SIGMOD, 2008.

Cited By

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  • (2019)Exploring market competition over topics in spatio-temporal document collectionsThe VLDB Journal — The International Journal on Very Large Data Bases10.1007/s00778-018-0522-928:1(123-145)Online publication date: 1-Feb-2019
  • (2018)From Opinions to RecommendationsSocial Information Access10.1007/978-3-319-90092-6_13(480-509)Online publication date: 3-May-2018
  • (2017)TweerAnalyzer: Twitter Trend Detection and Visualization2017 International Conference on Computing, Communication, Control and Automation (ICCUBEA)10.1109/ICCUBEA.2017.8463951(1-6)Online publication date: Aug-2017
  • Show More Cited By

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Information

Published In

cover image ACM Conferences
SIGMOD '09: Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
June 2009
1168 pages
ISBN:9781605585512
DOI:10.1145/1559845
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 29 June 2009

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Author Tags

  1. blogs
  2. social media
  3. text exploration
  4. text mining

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  • Demonstration

Conference

SIGMOD/PODS '09
Sponsor:
SIGMOD/PODS '09: International Conference on Management of Data
June 29 - July 2, 2009
Rhode Island, Providence, USA

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Overall Acceptance Rate 785 of 4,003 submissions, 20%

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Cited By

View all
  • (2019)Exploring market competition over topics in spatio-temporal document collectionsThe VLDB Journal — The International Journal on Very Large Data Bases10.1007/s00778-018-0522-928:1(123-145)Online publication date: 1-Feb-2019
  • (2018)From Opinions to RecommendationsSocial Information Access10.1007/978-3-319-90092-6_13(480-509)Online publication date: 3-May-2018
  • (2017)TweerAnalyzer: Twitter Trend Detection and Visualization2017 International Conference on Computing, Communication, Control and Automation (ICCUBEA)10.1109/ICCUBEA.2017.8463951(1-6)Online publication date: Aug-2017
  • (2016)Topic Exploration in Spatio-Temporal Document CollectionsProceedings of the 2016 International Conference on Management of Data10.1145/2882903.2882921(985-998)Online publication date: 26-Jun-2016
  • (2016)Online Social Networks Event Detection: A SurveySolving Large Scale Learning Tasks. Challenges and Algorithms10.1007/978-3-319-41706-6_1(1-41)Online publication date: 3-Jul-2016
  • (2015)Processing Social Media Messages in Mass EmergencyACM Computing Surveys10.1145/277158847:4(1-38)Online publication date: 26-Jun-2015
  • (2014)Scalable top-k spatio-temporal term querying2014 IEEE 30th International Conference on Data Engineering10.1109/ICDE.2014.6816647(148-159)Online publication date: Mar-2014
  • (2013)Dense subgraph maintenance under streaming edge weight updates for real-time story identificationThe VLDB Journal10.1007/s00778-013-0340-z23:2(175-199)Online publication date: 20-Oct-2013
  • (2013)Finding Critical Thresholds for Defining Bursts in Event LogsTransactions on Large-Scale Data- and Knowledge-Centered Systems VIII10.1007/978-3-642-37574-3_4(89-112)Online publication date: 2013
  • (2012)Dense subgraph maintenance under streaming edge weight updates for real-time story identificationProceedings of the VLDB Endowment10.14778/2168651.21686585:6(574-585)Online publication date: 1-Feb-2012
  • Show More Cited By

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