{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/108348"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/108348","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Topic mining and categorization in online discussion forums","abstract":"Online Forums provide a useful way to engage in discussions about a wide variety of topics, as well as gather custom information for which an exact source may not be available, using a combination of knowledge and human interpretation. Usually forums have categories which cater to a particular topic of interest, allowing information seekers and topic experts to meet. It is thus imperative to organize forum data into an organized structure. In this work we look at methods for categorizing forum posts into appropriate categories, where the number of such categories is large. We compare several baseline methods with state-of-the-art deep learning methods and analyze their performance. We observe that given the highly keyword-centric nature of our data, deep learning methods only slightly outperform baseline methods. Following this, we perform topic modeling on the forum data to find latent topics which creates a hierarchy across forum categories and clusters similar categories. In this process we observe that some of the recent approaches in topic modeling that utilize word embeddings lead to better topics. Finally, we use this hierarchy to perform hierarchical classification of the forum posts to allow better management of the classification task and analyze the benefits of this method.","abstract_html":"Online Forums provide a useful way to engage in discussions about a wide variety of topics, as well as gather custom information for which an exact source may not be available, using a combination of knowledge and human interpretation. Usually forums have categories which cater to a particular topic of interest, allowing information seekers and topic experts to meet. It is thus imperative to organize forum data into an organized structure. In this work we look at methods for categorizing forum posts into appropriate categories, where the number of such categories is large. We compare several baseline methods with state-of-the-art deep learning methods and analyze their performance. We observe that given the highly keyword-centric nature of our data, deep learning methods only slightly outperform baseline methods. Following this, we perform topic modeling on the forum data to find latent topics which creates a hierarchy across forum categories and clusters similar categories. In this process we observe that some of the recent approaches in topic modeling that utilize word embeddings lead to better topics. Finally, we use this hierarchy to perform hierarchical classification of the forum posts to allow better management of the classification task and analyze the benefits of this method.","abstract_has_math":false,"creators":["Dey, Jishnu"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Computer Science","degree_department":null,"school":null,"contributors":["Zhai, ChengXiang"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2020,"date_issued":"2020-08-27T00:51:33Z","date_published":"2020-08-27T00:51:33Z","updated_at":"2026-07-22T22:24:48Z","subjects":["discussion forums","topic modeling","text categorization","hierarchical categorization"],"languages":["en"],"rights":["Copyright 2020 Jishnu Dey"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/108348","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Zhai, ChengXiang"]},{"key":"dc:creator","label":"Author","values":["Dey, Jishnu"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2020-08-27T00:51:33Z","2022-08-27T00:51:40Z","2020-05-12","2020-05"]},{"key":"dc:type","label":"Dc Type","values":["text","Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer Science"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["discussion forums","topic modeling","text categorization","hierarchical categorization"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2020 Jishnu Dey"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/108348"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Online Forums provide a useful way to engage in discussions about a wide variety of topics, as well as gather custom information for which an exact source may not be available, using a combination of knowledge and human interpretation. Usually forums have categories which cater to a particular topic of interest, allowing information seekers and topic experts to meet. It is thus imperative to organize forum data into an organized structure. In this work we look at methods for categorizing forum posts into appropriate categories, where the number of such categories is large. We compare several baseline methods with state-of-the-art deep learning methods and analyze their performance. We observe that given the highly keyword-centric nature of our data, deep learning methods only slightly outperform baseline methods. Following this, we perform topic modeling on the forum data to find latent topics which creates a hierarchy across forum categories and clusters similar categories. In this process we observe that some of the recent approaches in topic modeling that utilize word embeddings lead to better topics. Finally, we use this hierarchy to perform hierarchical classification of the forum posts to allow better management of the classification task and analyze the benefits of this method.","Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2022-05-01","The student, Jishnu Dey, accepted the attached license on 2020-05-12 at 13:28.","The student, Jishnu Dey, submitted this Thesis for approval on 2020-05-12 at 13:30.","This Thesis was approved for publication on 2020-05-12 at 14:23.","DSpace SAF Submission Ingestion Package generated from Vireo submission #15355 on 2020-08-25 at 17:44:24","Made available in DSpace on 2020-08-27T00:51:33Z (GMT). No. of bitstreams: 2 DEY-THESIS-2020.pdf: 5485995 bytes, checksum: 6da71fbb7e5d0cde6e311be078035b31 (MD5) LICENSE.txt: 4207 bytes, checksum: e109a493d176b0bdabd1164bb4b4bb52 (MD5) Previous issue date: 2020-05-12","Embargo set by: Seth Robbins for item 115963 Lift date: 2022-08-27T00:51:40Z Reason: Author requested closed access (OA after 2yrs) in Vireo ETD system","Author requested closed access (OA after 2yrs) in Vireo ETD system","Limited"]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Topic mining and categorization in online discussion forums"]}]}],"canonical_facts":{"dc:contributor":["Zhai, ChengXiang"],"dc:creator":["Dey, Jishnu"],"dc:date":["2020-08-27T00:51:33Z","2022-08-27T00:51:40Z","2020-05-12","2020-05"],"dc:description":["Online Forums provide a useful way to engage in discussions about a wide variety of topics, as well as gather custom information for which an exact source may not be available, using a combination of knowledge and human interpretation. Usually forums have categories which cater to a particular topic of interest, allowing information seekers and topic experts to meet. It is thus imperative to organize forum data into an organized structure. In this work we look at methods for categorizing forum posts into appropriate categories, where the number of such categories is large. We compare several baseline methods with state-of-the-art deep learning methods and analyze their performance. We observe that given the highly keyword-centric nature of our data, deep learning methods only slightly outperform baseline methods. Following this, we perform topic modeling on the forum data to find latent topics which creates a hierarchy across forum categories and clusters similar categories. In this process we observe that some of the recent approaches in topic modeling that utilize word embeddings lead to better topics. Finally, we use this hierarchy to perform hierarchical classification of the forum posts to allow better management of the classification task and analyze the benefits of this method.","Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2022-05-01","The student, Jishnu Dey, accepted the attached license on 2020-05-12 at 13:28.","The student, Jishnu Dey, submitted this Thesis for approval on 2020-05-12 at 13:30.","This Thesis was approved for publication on 2020-05-12 at 14:23.","DSpace SAF Submission Ingestion Package generated from Vireo submission #15355 on 2020-08-25 at 17:44:24","Made available in DSpace on 2020-08-27T00:51:33Z (GMT). No. of bitstreams: 2 DEY-THESIS-2020.pdf: 5485995 bytes, checksum: 6da71fbb7e5d0cde6e311be078035b31 (MD5) LICENSE.txt: 4207 bytes, checksum: e109a493d176b0bdabd1164bb4b4bb52 (MD5) Previous issue date: 2020-05-12","Embargo set by: Seth Robbins for item 115963 Lift date: 2022-08-27T00:51:40Z Reason: Author requested closed access (OA after 2yrs) in Vireo ETD system","Author requested closed access (OA after 2yrs) in Vireo ETD system","Limited"],"dc:format":["application/pdf"],"dc:identifier":["http://hdl.handle.net/2142/108348"],"dc:language":["en"],"dc:rights":["Copyright 2020 Jishnu Dey"],"dc:subject":["discussion forums","topic modeling","text categorization","hierarchical categorization"],"dc:title":["Topic mining and categorization in online discussion forums"],"dc:type":["text","Thesis"],"thesis:degree_discipline":["Computer Science"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:24:48Z"}