{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,16]],"date-time":"2026-01-16T18:18:05Z","timestamp":1768587485142,"version":"3.49.0"},"reference-count":66,"publisher":"Association for Computing Machinery (ACM)","issue":"1","license":[{"start":{"date-parts":[[2013,12,1]],"date-time":"2013-12-01T00:00:00Z","timestamp":1385856000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Intell. Syst. Technol."],"published-print":{"date-parts":[[2013,12]]},"abstract":"<jats:p>In this manuscript, we study the problem of detecting coordinated free text campaigns in large-scale social media. These campaigns\u2014ranging from coordinated spam messages to promotional and advertising campaigns to political astro-turfing\u2014are growing in significance and reach with the commensurate rise in massive-scale social systems. Specifically, we propose and evaluate a content-driven framework for effectively linking free text posts with common \u201ctalking points\u201d and extracting campaigns from large-scale social media. Three of the salient features of the campaign extraction framework are: (i) first, we investigate graph mining techniques for isolating coherent campaigns from large message-based graphs; (ii) second, we conduct a comprehensive comparative study of text-based message correlation in message and user levels; and (iii) finally, we analyze temporal behaviors of various campaign types. Through an experimental study over millions of Twitter messages we identify five major types of campaigns\u2014namely Spam, Promotion, Template, News, and Celebrity campaigns\u2014and we show how these campaigns may be extracted with high precision and recall.<\/jats:p>","DOI":"10.1145\/2542182.2542191","type":"journal-article","created":{"date-parts":[[2014,1,2]],"date-time":"2014-01-02T13:09:43Z","timestamp":1388668183000},"page":"1-28","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":27,"title":["Campaign extraction from social media"],"prefix":"10.1145","volume":"5","author":[{"given":"Kyumin","family":"Lee","sequence":"first","affiliation":[{"name":"Texas A&amp;M University, College Station, TX"}]},{"given":"James","family":"Caverlee","sequence":"additional","affiliation":[{"name":"Texas A&amp;M University, College Station, TX"}]},{"given":"Zhiyuan","family":"Cheng","sequence":"additional","affiliation":[{"name":"Texas A&amp;M University, College Station, TX"}]},{"given":"Daniel Z.","family":"Sui","sequence":"additional","affiliation":[{"name":"Ohio State University, College Station, TX"}]}],"member":"320","published-online":{"date-parts":[[2014,1,3]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"Apache. 2012. Hadoop. http:\/\/hadoop.apache.org\/.  Apache. 2012. Hadoop. http:\/\/hadoop.apache.org\/."},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/1326561.1326563"},{"key":"e_1_2_1_3_1","volume-title":"Proceedings of the SIGIR Workshop on Adversarial Information Retrieval on the Web.","author":"Benczur A. A.","unstructured":"Benczur , A. A. , Csalogany , K. , and Sarlos , T . 2006. Link-based similarity search to fight web spam . In Proceedings of the SIGIR Workshop on Adversarial Information Retrieval on the Web. Benczur, A. A., Csalogany, K., and Sarlos, T. 2006. Link-based similarity search to fight web spam. In Proceedings of the SIGIR Workshop on Adversarial Information Retrieval on the Web."},{"key":"e_1_2_1_4_1","volume-title":"Proceedings of the Collaboration, Electronic Messaging, Anti-Abuse and Spam Conference (CEAS'10)","author":"Benevenuto F.","unstructured":"Benevenuto , F. , Magno , G. , Rodrigues , T. , and Almeida , V . 2010. Detecting spammers on twitter . In Proceedings of the Collaboration, Electronic Messaging, Anti-Abuse and Spam Conference (CEAS'10) . Benevenuto, F., Magno, G., Rodrigues, T., and Almeida, V. 2010. Detecting spammers on twitter. In Proceedings of the Collaboration, Electronic Messaging, Anti-Abuse and Spam Conference (CEAS'10)."},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/1571941.1572047"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.5555\/1248547.1248644"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0169-7552(97)00031-7"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/1963405.1963500"},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/1378889.1378908"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2009.06.027"},{"key":"e_1_2_1_11_1","unstructured":"Cctv. 2010. Uncovering online promotion. http:\/\/news.cntv.cn\/china\/20101107\/102619.shtml.  Cctv. 2010. Uncovering online promotion. http:\/\/news.cntv.cn\/china\/20101107\/102619.shtml."},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/1871437.1871535"},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/506309.506311"},{"key":"e_1_2_1_14_1","volume-title":"Influence: The Psychology of Persuasion (Collins Business Essentials)","author":"Cialdini R. B.","year":"2007","unstructured":"Cialdini , R. B. 2007 . Influence: The Psychology of Persuasion (Collins Business Essentials) . Harper Paperbacks . Cialdini, R. B. 2007. Influence: The Psychology of Persuasion (Collins Business Essentials). Harper Paperbacks."},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1561\/1500000006"},{"key":"e_1_2_1_16_1","volume-title":"Proceedings of the 6th Conference on Operating Systems Design and Implementation (OSDI'04)","author":"Dean J.","unstructured":"Dean , J. and Ghemawat , S . 2004. Mapreduce: Simplified data processing on large clusters . In Proceedings of the 6th Conference on Operating Systems Design and Implementation (OSDI'04) . Dean, J. and Ghemawat, S. 2004. Mapreduce: Simplified data processing on large clusters. In Proceedings of the 6th Conference on Operating Systems Design and Implementation (OSDI'04)."},{"key":"e_1_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/1017074.1017077"},{"key":"e_1_2_1_18_1","unstructured":"Films L. 2011. (Astro) turf wars. www.astroturfwars.com.  Films L. 2011. (Astro) turf wars. www.astroturfwars.com."},{"key":"e_1_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/1879141.1879147"},{"key":"e_1_2_1_20_1","volume-title":"Proceedings of the 31st International Conference on Very Large Data Bases (VLDB'05)","author":"Gibson D.","unstructured":"Gibson , D. , Kumar , R. , and Tomkins , A . 2005. Discovering large dense subgraphs in massive graphs . In Proceedings of the 31st International Conference on Very Large Data Bases (VLDB'05) . 721--732. Gibson, D., Kumar, R., and Tomkins, A. 2005. Discovering large dense subgraphs in massive graphs. In Proceedings of the 31st International Conference on Very Large Data Bases (VLDB'05). 721--732."},{"key":"e_1_2_1_21_1","unstructured":"Gilbert I. and Henry T. 2010. Persuasion detection in conversation. In Master's thesis Naval Postgraduate School Monterey CA.  Gilbert I. and Henry T. 2010. Persuasion detection in conversation. In Master's thesis Naval Postgraduate School Monterey CA."},{"key":"e_1_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/1866307.1866311"},{"key":"e_1_2_1_23_1","volume-title":"Proceedings of the 32nd International Conference on Very Large Data Bases (VLDB'06)","author":"Gyongyi Z.","unstructured":"Gyongyi , Z. , Berkhin , P. , Garcia-Molina , H. , and Pedersen , J . 2006. Link spam detection based on mass estimation . In Proceedings of the 32nd International Conference on Very Large Data Bases (VLDB'06) . 439--450. Gyongyi, Z., Berkhin, P., Garcia-Molina, H., and Pedersen, J. 2006. Link spam detection based on mass estimation. In Proceedings of the 32nd International Conference on Very Large Data Bases (VLDB'06). 439--450."},{"key":"e_1_2_1_24_1","volume-title":"Proceedings of the 30th International Conference on Very Large Data Bases (VLDB'04)","author":"Gyongyi Z.","unstructured":"Gyongyi , Z. , Garcia-Molina , H. , and Pedersen , J . 2004. Combating web spam with trustrank . In Proceedings of the 30th International Conference on Very Large Data Bases (VLDB'04) . 576--587. Gyongyi, Z., Garcia-Molina, H., and Pedersen, J. 2004. Combating web spam with trustrank. In Proceedings of the 30th International Conference on Very Large Data Bases (VLDB'04). 576--587."},{"key":"e_1_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/bti1049"},{"key":"e_1_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/MIS.2007.44"},{"key":"e_1_2_1_27_1","volume-title":"Anti-Abuse and Spam Conference (CEAS'10)","author":"Irani D.","unstructured":"Irani , D. , Webb , S. , Pu , C. , and Li , K . 2010. Study of trend-stuffing on twitter through text classification. In Collaboration, Electronic Messaging , Anti-Abuse and Spam Conference (CEAS'10) . Irani, D., Webb, S., Pu, C., and Li, K. 2010. Study of trend-stuffing on twitter through text classification. In Collaboration, Electronic Messaging, Anti-Abuse and Spam Conference (CEAS'10)."},{"key":"e_1_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/1409220.1409225"},{"key":"e_1_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/988672.988726"},{"key":"e_1_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/2063576.2063658"},{"key":"e_1_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1145\/1835449.1835522"},{"key":"e_1_2_1_32_1","volume-title":"Proceedings of the 5th AAAI International Conference on Weblogs and Social Media (ICWSM'11)","author":"Lee K.","unstructured":"Lee , K. , Eoff , B. D. , and Caverlee , J . 2011b. Seven months with the devils: A long-term study of content polluters on twitter . In Proceedings of the 5th AAAI International Conference on Weblogs and Social Media (ICWSM'11) . Lee, K., Eoff, B. D., and Caverlee, J. 2011b. Seven months with the devils: A long-term study of content polluters on twitter. In Proceedings of the 5th AAAI International Conference on Weblogs and Social Media (ICWSM'11)."},{"key":"e_1_2_1_33_1","first-page":"707","article-title":"Binary codes capable of correcting deletions, insertions and reversals","volume":"10","author":"Levenshtein V.","year":"1966","unstructured":"Levenshtein , V. 1966 . Binary codes capable of correcting deletions, insertions and reversals . Soviet Phys. Doklady 10 , 707 . Levenshtein, V. 1966. Binary codes capable of correcting deletions, insertions and reversals. Soviet Phys. Doklady 10, 707.","journal-title":"Soviet Phys. Doklady"},{"key":"e_1_2_1_34_1","volume-title":"Proceedings of the 7th USENIX Security Symposium.","author":"Levien R.","unstructured":"Levien , R. and Aiken , A . 1998. Attack-resistant trust metrics for public key certification . In Proceedings of the 7th USENIX Security Symposium. Levien, R. and Aiken, A. 1998. Attack-resistant trust metrics for public key certification. In Proceedings of the 7th USENIX Security Symposium."},{"key":"e_1_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1145\/1871437.1871557"},{"key":"e_1_2_1_36_1","doi-asserted-by":"crossref","unstructured":"Manning C. D. Raghavan P. and Schtze H. 2008. Introduction to Information Retrieval. Cambridge University Press.   Manning C. D. Raghavan P. and Schtze H. 2008. Introduction to Information Retrieval. Cambridge University Press.","DOI":"10.1017\/CBO9780511809071"},{"key":"e_1_2_1_37_1","unstructured":"Manning C. D. and Schutze H. 1999. Foundations of Statistical Natural Language Processing. MIT Press.   Manning C. D. and Schutze H. 1999. Foundations of Statistical Natural Language Processing. MIT Press."},{"key":"e_1_2_1_38_1","volume-title":"Proceedings of the 22nd National Conference on Artificial Intelligence (AAAI'07)","author":"Mehta B.","year":"2007","unstructured":"Mehta , B. 2007 . Unsupervised shilling detection for collaborative filtering . In Proceedings of the 22nd National Conference on Artificial Intelligence (AAAI'07) . Mehta, B. 2007. Unsupervised shilling detection for collaborative filtering. In Proceedings of the 22nd National Conference on Artificial Intelligence (AAAI'07)."},{"key":"e_1_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1145\/1216295.1216307"},{"key":"e_1_2_1_40_1","volume-title":"Proceedings of the 20th USENIX Security Symposium.","author":"Motoyama M.","unstructured":"Motoyama , M. , McCoy , D. , Levchenko , K. , Savage , S. , and Voelker , G. M . 2011. Dirty jobs: The role of freelance labor in web service abuse . In Proceedings of the 20th USENIX Security Symposium. Motoyama, M., McCoy, D., Levchenko, K., Savage, S., and Voelker, G. M. 2011. Dirty jobs: The role of freelance labor in web service abuse. In Proceedings of the 20th USENIX Security Symposium."},{"key":"e_1_2_1_41_1","volume-title":"Proceedings of the 35th Annual Hawaii International Conference on System Sciences (HICSS'02)","author":"Mui L.","unstructured":"Mui , L. , Mohtashemi , M. , and Halberstadt , A . 2002. A computational model of trust and reputation for e-business . In Proceedings of the 35th Annual Hawaii International Conference on System Sciences (HICSS'02) . 188. Mui, L., Mohtashemi, M., and Halberstadt, A. 2002. A computational model of trust and reputation for e-business. In Proceedings of the 35th Annual Hawaii International Conference on System Sciences (HICSS'02). 188."},{"key":"e_1_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1145\/1963192.1963240"},{"key":"e_1_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-72584-8_68"},{"key":"e_1_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.1145\/1135777.1135794"},{"key":"e_1_2_1_45_1","volume-title":"Proceedings of the 13th International Conference on Database and Expert Systems Applications (DEXA'02)","author":"O'Mahony M.","unstructured":"O'Mahony , M. , Hurley , N. , and Silvestre , G . 2002. Promoting recommendations: An attack on collaborative filtering . In Proceedings of the 13th International Conference on Database and Expert Systems Applications (DEXA'02) . 494--503. O'Mahony, M., Hurley, N., and Silvestre, G. 2002. Promoting recommendations: An attack on collaborative filtering. In Proceedings of the 13th International Conference on Database and Expert Systems Applications (DEXA'02). 494--503."},{"key":"e_1_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2010.09.013"},{"key":"e_1_2_1_47_1","volume-title":"Proceedings of the 5th AAAI International Conference on Weblogs and Social Media (ICWSM'11)","author":"Ratkiewicz J.","unstructured":"Ratkiewicz , J. , Conover , M. , Meiss , M. , Goncalves , B. , Flammini , A. , and Menczer , F . 2011. Detecting and tracking political abuse in social media . In Proceedings of the 5th AAAI International Conference on Weblogs and Social Media (ICWSM'11) . Ratkiewicz, J., Conover, M., Meiss, M., Goncalves, B., Flammini, A., and Menczer, F. 2011. Detecting and tracking political abuse in social media. In Proceedings of the 5th AAAI International Conference on Weblogs and Social Media (ICWSM'11)."},{"key":"e_1_2_1_48_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-01718-6_8"},{"key":"e_1_2_1_49_1","volume-title":"Proceedings of the ICML Workshop on Learning for Text Categorization.","author":"Sahami M.","unstructured":"Sahami , M. , Dumais , S. , Heckerman , D. , and Horvitz , E . 1998. A bayesian approach to filtering junk e-mail . In Proceedings of the ICML Workshop on Learning for Text Categorization. Sahami, M., Dumais, S., Heckerman, D., and Horvitz, E. 1998. A bayesian approach to filtering junk e-mail. In Proceedings of the ICML Workshop on Learning for Text Categorization."},{"key":"e_1_2_1_50_1","doi-asserted-by":"publisher","DOI":"10.1145\/1062745.1062818"},{"key":"e_1_2_1_51_1","doi-asserted-by":"publisher","DOI":"10.1145\/1390334.1390431"},{"key":"e_1_2_1_52_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.tcs.2006.06.015"},{"key":"e_1_2_1_53_1","unstructured":"Trec. 2004. Terabyte track. http:\/\/www-nlpir.nist.gov\/projects\/terabyte\/.  Trec. 2004. Terabyte track. http:\/\/www-nlpir.nist.gov\/projects\/terabyte\/."},{"key":"e_1_2_1_54_1","unstructured":"Trec. 2007. Spam track. http:\/\/plg.uwaterloo.ca\/&sim;gvcormac\/treccorpus07\/.  Trec. 2007. Spam track. http:\/\/plg.uwaterloo.ca\/&sim;gvcormac\/treccorpus07\/."},{"key":"e_1_2_1_55_1","unstructured":"Twitter. 2012. The twitter rules. http:\/\/support.twitter.com\/articles\/18311-the-twitter-rules.  Twitter. 2012. The twitter rules. http:\/\/support.twitter.com\/articles\/18311-the-twitter-rules."},{"key":"e_1_2_1_56_1","doi-asserted-by":"publisher","DOI":"10.6028\/NIST.SP.500-246"},{"key":"e_1_2_1_57_1","doi-asserted-by":"publisher","DOI":"10.1145\/2187836.2187928"},{"key":"e_1_2_1_58_1","doi-asserted-by":"publisher","DOI":"10.1145\/1376616.1376663"},{"key":"e_1_2_1_59_1","volume-title":"Proceedings of the Conference on Email and Anti-Spam (CEAS'06)","author":"Webb S.","unstructured":"Webb , S. , Caverlee , J. , and Pu , C . 2006. Introducing the webb spam corpus: Using email spam to identify web spam automatically . In Proceedings of the Conference on Email and Anti-Spam (CEAS'06) . Webb, S., Caverlee, J., and Pu, C. 2006. Introducing the webb spam corpus: Using email spam to identify web spam automatically. In Proceedings of the Conference on Email and Anti-Spam (CEAS'06)."},{"key":"e_1_2_1_60_1","doi-asserted-by":"publisher","DOI":"10.1145\/1062745.1062762"},{"key":"e_1_2_1_61_1","doi-asserted-by":"publisher","DOI":"10.1109\/FCST.2009.30"},{"key":"e_1_2_1_62_1","doi-asserted-by":"publisher","DOI":"10.1145\/1964858.1964860"},{"key":"e_1_2_1_63_1","doi-asserted-by":"publisher","DOI":"10.1145\/1014052.1014107"},{"key":"e_1_2_1_64_1","volume-title":"Proceedings of the 25th Workshops at the AAAI Conference on Artificial Intelligence.","author":"Young J.","year":"2011","unstructured":"Young , J. , Martell , C. , Anand , P. , Ortiz , P. , and Gilbert Iv , H. 2011 . A microtext corpus for persuasion detection in dialog . In Proceedings of the 25th Workshops at the AAAI Conference on Artificial Intelligence. Young, J., Martell, C., Anand, P., Ortiz, P., and Gilbert Iv, H. 2011. A microtext corpus for persuasion detection in dialog. In Proceedings of the 25th Workshops at the AAAI Conference on Artificial Intelligence."},{"key":"e_1_2_1_65_1","doi-asserted-by":"publisher","DOI":"10.1145\/1835449.1835562"},{"key":"e_1_2_1_66_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10796-005-4807-3"}],"container-title":["ACM Transactions on Intelligent Systems and Technology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/2542182.2542191","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/2542182.2542191","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T08:09:56Z","timestamp":1750234196000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/2542182.2542191"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013,12]]},"references-count":66,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2013,12]]}},"alternative-id":["10.1145\/2542182.2542191"],"URL":"https:\/\/doi.org\/10.1145\/2542182.2542191","relation":{},"ISSN":["2157-6904","2157-6912"],"issn-type":[{"value":"2157-6904","type":"print"},{"value":"2157-6912","type":"electronic"}],"subject":[],"published":{"date-parts":[[2013,12]]},"assertion":[{"value":"2012-02-01","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2012-09-01","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2014-01-03","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}