2026-09-21T09:04:31Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/101215 2023-07-11 col_2142_5131 col_2142_10761 com_2142_5130 com_2142_10755 com_2142_234

Han, Jiawei Lei, Dongming 2018-09-04T20:36:52Z 2018-09-04T20:36:52Z 2020-09-05T09:15:16Z 2018-04-24 2018-05 The real-time discovery of local events (e.g., protests, disasters) has been widely recognized as a fundamental socioeconomic task. Recent studies have demonstrated that the geo-tagged tweet stream serves as an unprecedentedly valuable source for local event detection. Nevertheless, how to effectively extract local events from massive geo-tagged tweet streams in real time remains challenging. To bridge the gap, we propose a method for effective and real-time local event detection from geo-tagged tweet streams. Our method, named GeoBurst+, first leverages a novel cross-modal authority measure to identify several pivots in the query window. Such pivots reveal different geo-topical activities and naturally attract similar tweets to form candidate events. GeoBurst+ further summarizes the continuous stream and compares the candidates against the historical summaries to pinpoint truly interesting local events. Better still, as the query window shifts, GeoBurst+ is capable of updating the event list with little time cost, thus achieving continuous monitoring of the stream. We used crowdsourcing to evaluate GeoBurst+ on two million-scale data sets, and found it significantly more effective than existing methods while being orders of magnitude faster. Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2020-05-01 The student, Dongming Lei, accepted the attached license on 2018-04-23 at 23:16. The student, Dongming Lei, submitted this Thesis for approval on 2018-04-23 at 23:26. This Thesis was approved for publication on 2018-04-24 at 08:34. DSpace SAF Submission Ingestion Package generated from Vireo submission #12439 on 2018-08-31 at 17:21:20 Made available in DSpace on 2018-09-04T20:36:52Z (GMT). No. of bitstreams: 2 LEI-THESIS-2018.pdf: 3970025 bytes, checksum: 754b46b687079ee585ae0b3d2615efd0 (MD5) LICENSE.txt: 4209 bytes, checksum: 6439fc6211186a959779f68c1ca7ce8e (MD5) Previous issue date: 2018-04-24 Embargo set by: Seth Robbins for item 107299 Lift date: 2020-09-04T20:37:00Z Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD system Embargo set by: Seth Robbins for item 107299 Lift date: 2020-09-04T20:42:08Z Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD system U of I Only Restriction Lifted for Item 107299 on 2020-09-05T09:15:16Z. application/pdf http://hdl.handle.net/2142/101215 en Copyright 2018 Dongming Lei event detection social media local event Local event detection in geo-tagged tweet streams text text Computer Science Computer Science University of Illinois at Urbana-Champaign Thesis M.S.