Social Media Analytics for Radical Opinion Mining in Hate Group Web Forums
Web forums are frequently used as platforms for the exchange of information and opinions as well as propaganda dissemination. But online content can be misused when the information being distributed, such as radical opinions, is unsolicited or inappropriate. This study introduces a technique that co...
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Veröffentlicht in: | Journal of homeland security and emergency management 2011-01, Vol.8 (1), p.1 |
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container_title | Journal of homeland security and emergency management |
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creator | Yang, Ming Kiang, Melody Ku, Yungchang Chiu, Chaochang Li, Yijun |
description | Web forums are frequently used as platforms for the exchange of information and opinions as well as propaganda dissemination. But online content can be misused when the information being distributed, such as radical opinions, is unsolicited or inappropriate. This study introduces a technique that combines machine learning and semantic-oriented approaches to identify radical opinions in hate group Web forums. Four types of text features (syntactic, stylistic, content-specific, and lexicon features) are extracted as text classification predictors, and three classification techniques (SVM, Naïve Bayes, and Adaboost) are implemented. Postings from two hate group Web forums are collected and the preliminary results are encouraging. In addition, cross-validation indicates the proposed technique is stable and extendible to timeframes beyond that of the training data. The proposed technique can also be an effective tool for other sentiment classification problems. |
doi_str_mv | 10.2202/1547-7355.1801 |
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The proposed technique can also be an effective tool for other sentiment classification problems.</description><identifier>ISSN: 2194-6361</identifier><identifier>ISSN: 1547-7355</identifier><identifier>EISSN: 1547-7355</identifier><identifier>DOI: 10.2202/1547-7355.1801</identifier><language>eng</language><publisher>Berlin: De Gruyter</publisher><subject>Bayesian analysis ; Classification ; Cognitive style ; Communication ; Data mining ; Digital media ; Discourse analysis ; Dissemination ; Feature extraction ; Hate ; Hatred ; Inappropriateness ; Internet ; Learning algorithms ; Machine learning ; Mining ; National security ; Opinion ; Propaganda ; Public opinion ; radical opinion mining ; Radicalism ; Sentiment analysis ; sentiment classification ; Social media ; social media analytics ; Social networks ; Validity ; Web analytics ; Web forums ; Webs</subject><ispartof>Journal of homeland security and emergency management, 2011-01, Vol.8 (1), p.1</ispartof><rights>2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston</rights><rights>Copyright Berkeley Electronic Press Jan 2011</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c413t-312d01915a24cab2eddd315b9606bd2e76489afa5a92dbd1c9fb2a6a2a75ac4a3</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.degruyter.com/document/doi/10.2202/1547-7355.1801/pdf$$EPDF$$P50$$Gwalterdegruyter$$H</linktopdf><linktohtml>$$Uhttps://www.degruyter.com/document/doi/10.2202/1547-7355.1801/html$$EHTML$$P50$$Gwalterdegruyter$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,66497,68281</link.rule.ids></links><search><creatorcontrib>Yang, Ming</creatorcontrib><creatorcontrib>Kiang, Melody</creatorcontrib><creatorcontrib>Ku, Yungchang</creatorcontrib><creatorcontrib>Chiu, Chaochang</creatorcontrib><creatorcontrib>Li, Yijun</creatorcontrib><title>Social Media Analytics for Radical Opinion Mining in Hate Group Web Forums</title><title>Journal of homeland security and emergency management</title><description>Web forums are frequently used as platforms for the exchange of information and opinions as well as propaganda dissemination. But online content can be misused when the information being distributed, such as radical opinions, is unsolicited or inappropriate. This study introduces a technique that combines machine learning and semantic-oriented approaches to identify radical opinions in hate group Web forums. Four types of text features (syntactic, stylistic, content-specific, and lexicon features) are extracted as text classification predictors, and three classification techniques (SVM, Naïve Bayes, and Adaboost) are implemented. Postings from two hate group Web forums are collected and the preliminary results are encouraging. In addition, cross-validation indicates the proposed technique is stable and extendible to timeframes beyond that of the training data. The proposed technique can also be an effective tool for other sentiment classification problems.</description><subject>Bayesian analysis</subject><subject>Classification</subject><subject>Cognitive style</subject><subject>Communication</subject><subject>Data mining</subject><subject>Digital media</subject><subject>Discourse analysis</subject><subject>Dissemination</subject><subject>Feature extraction</subject><subject>Hate</subject><subject>Hatred</subject><subject>Inappropriateness</subject><subject>Internet</subject><subject>Learning algorithms</subject><subject>Machine learning</subject><subject>Mining</subject><subject>National security</subject><subject>Opinion</subject><subject>Propaganda</subject><subject>Public opinion</subject><subject>radical opinion mining</subject><subject>Radicalism</subject><subject>Sentiment analysis</subject><subject>sentiment classification</subject><subject>Social media</subject><subject>social media analytics</subject><subject>Social networks</subject><subject>Validity</subject><subject>Web analytics</subject><subject>Web forums</subject><subject>Webs</subject><issn>2194-6361</issn><issn>1547-7355</issn><issn>1547-7355</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><sourceid>7UB</sourceid><recordid>eNp1kEFvFCEYhonRxLV69Uz04GlWPhiY4dis3VbTplHXeCTfANNQZ4cVZqL772WypiZGTx-B53mBl5CXwNacM_4WZN1UjZByDS2DR2T1sPGYrDjoulJCwVPyLOd7xrgUTKzIh8_RBhzojXcB6fmIw3EKNtM-JvoJXbDl7PYQxhBHelPGeEfDSK9w8vQyxflAv_qObmOa9_k5edLjkP2L3_OMfNle7DZX1fXt5fvN-XVlaxBTJYA7Bhok8tpix71zToDstGKqc9w3qm419ihRc9c5sLrvOCrk2Ei0NYoz8uaUe0jx--zzZPYhWz8MOPo4Z9OWJGgBRCFf_UXexzmVP2ajuWgkU1oX6PX_IF4zxqSSLSvU-kTZFHNOvjeHFPaYjgaYWeo3S9tmadss9RehPQk_cJh8cv4uzcey-JP-b7Fd1Oqkhjz5nw8XYfpmVFOebT7uarPdSGC7d2BA_AJeBpXY</recordid><startdate>20110101</startdate><enddate>20110101</enddate><creator>Yang, Ming</creator><creator>Kiang, Melody</creator><creator>Ku, Yungchang</creator><creator>Chiu, Chaochang</creator><creator>Li, Yijun</creator><general>De Gruyter</general><general>Walter De Gruyter & Company</general><scope>BSCLL</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7T2</scope><scope>7TA</scope><scope>7TB</scope><scope>7UB</scope><scope>8BJ</scope><scope>8FD</scope><scope>C1K</scope><scope>FQK</scope><scope>FR3</scope><scope>H8D</scope><scope>JBE</scope><scope>JG9</scope><scope>K7.</scope><scope>KR7</scope><scope>L7M</scope></search><sort><creationdate>20110101</creationdate><title>Social Media Analytics for Radical Opinion Mining in Hate Group Web Forums</title><author>Yang, Ming ; 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subjects | Bayesian analysis Classification Cognitive style Communication Data mining Digital media Discourse analysis Dissemination Feature extraction Hate Hatred Inappropriateness Internet Learning algorithms Machine learning Mining National security Opinion Propaganda Public opinion radical opinion mining Radicalism Sentiment analysis sentiment classification Social media social media analytics Social networks Validity Web analytics Web forums Webs |
title | Social Media Analytics for Radical Opinion Mining in Hate Group Web Forums |
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