This work addresses one important problem in Social Networks Analysis, namely link prediction. Link Prediction is important to understand and evaluate the change in structure for a certain social network over a given period of time. While different methods exist to address link prediction in this work we explore one such method, which is termed Closure Analysis. We work on two real social networks, Facebook and Wikipedia; while these two networks have very different properties the application of one link prediction method is different for each network. We study the application of this method on the two networks and examine the network change this brings over a period of time. This work also considers one influential factor, namely the most active people in the community.
Keywords: Artificial Intelligence, Social network, Information network, digraph, Closure Analysis, Connections, Influential node, network structure
","abstract_html":"<p>This work addresses one important problem in Social Networks Analysis, namely link prediction. Link Prediction is important to understand and evaluate the change in structure for a certain social network over a given period of time. While different methods exist to address link prediction in this work we explore one such method, which is termed Closure Analysis. We work on two real social networks, Facebook and Wikipedia; while these two networks have very different properties the application of one link prediction method is different for each network. We study the application of this method on the two networks and examine the network change this brings over a period of time. This work also considers one influential factor, namely the most active people in the community.</p><p>Keywords: Artificial Intelligence, Social network, Information network, digraph, Closure Analysis, Connections, Influential node, network structure</p>","abstract_has_math":false,"creators":["Munimadugu, Hareendra"],"institution":"University of Cincinnati","degree_name":"MS","degree_level":"masters","degree_discipline":"Engineering and Applied Science: Computer Engineering","degree_department":null,"school":null,"contributors":["Ralescu, Anca"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2012,"date_issued":"2012","date_published":"2012","updated_at":"2026-07-24T03:36:23Z","subjects":["Computer Engineering"],"languages":["English"],"rights":["unrestricted","This thesis or dissertation is protected by copyright: all rights reserved. It may not be copied or redistributed beyond the terms of applicable copyright laws."],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://rave.ohiolink.edu/etdc/view?acc_num=ucin1353099669","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Ralescu, Anca"]},{"key":"dc:creator","label":"Author","values":["Munimadugu, Hareendra"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2012"]},{"key":"dc:publisher","label":"Institution","values":["University of Cincinnati / OhioLINK"]},{"key":"dc:type","label":"Dc Type","values":["Electronic Thesis or Dissertation"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Engineering and Applied Science: Computer Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["masters"]},{"key":"thesis:degree_name","label":"Degree Name","values":["MS"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Cincinnati"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Computer Engineering"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["English"]},{"key":"dc:rights","label":"Dc Rights","values":["unrestricted","This thesis or dissertation is protected by copyright: all rights reserved. It may not be copied or redistributed beyond the terms of applicable copyright laws."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://rave.ohiolink.edu/etdc/view?acc_num=ucin1353099669"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["This work addresses one important problem in Social Networks Analysis, namely link prediction. Link Prediction is important to understand and evaluate the change in structure for a certain social network over a given period of time. While different methods exist to address link prediction in this work we explore one such method, which is termed Closure Analysis. We work on two real social networks, Facebook and Wikipedia; while these two networks have very different properties the application of one link prediction method is different for each network. We study the application of this method on the two networks and examine the network change this brings over a period of time. This work also considers one influential factor, namely the most active people in the community.
Keywords: Artificial Intelligence, Social network, Information network, digraph, Closure Analysis, Connections, Influential node, network structure
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Keywords: Artificial Intelligence, Social network, Information network, digraph, Closure Analysis, Connections, Influential node, network structure
"],"dc:format":["application/pdf","p.62","366.4 KB"],"dc:identifier":["http://rave.ohiolink.edu/etdc/view?acc_num=ucin1353099669"],"dc:language":["English"],"dc:publisher":["University of Cincinnati / OhioLINK"],"dc:rights":["unrestricted","This thesis or dissertation is protected by copyright: all rights reserved. It may not be copied or redistributed beyond the terms of applicable copyright laws."],"dc:subject":["Computer Engineering"],"dc:title":["Tie Inducement using Closure Analysis in Information Networks"],"dc:type":["Electronic Thesis or Dissertation"],"thesis:degree_discipline":["Engineering and Applied Science: Computer Engineering"],"thesis:degree_level":["masters"],"thesis:degree_name":["MS"],"thesis:institution_name":["University of Cincinnati"]},"updated_at":"2026-07-24T03:36:23Z"}