Finding Emotional-Laden Resources on the World Wide Web
Some content in multimedia resources can depict or evoke certain emotions in users. The aim of Emotional Information Retrieval (EmIR) and of our research is to identify knowledge about emotional-laden documents and to use these findings in a new kind of World Wide Web information service that allows...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2011-03-01
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| Series: | Information |
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| Online Access: | http://www.mdpi.com/2078-2489/2/1/217/ |
| _version_ | 1811275249734385664 |
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| author | Diane Rasmussen Neal Stefanie Schmidt Tobias Siebenlist Wolfgang G. Stock Kathrin Knautz |
| author_facet | Diane Rasmussen Neal Stefanie Schmidt Tobias Siebenlist Wolfgang G. Stock Kathrin Knautz |
| author_sort | Diane Rasmussen Neal |
| collection | DOAJ |
| description | Some content in multimedia resources can depict or evoke certain emotions in users. The aim of Emotional Information Retrieval (EmIR) and of our research is to identify knowledge about emotional-laden documents and to use these findings in a new kind of World Wide Web information service that allows users to search and browse by emotion. Our prototype, called Media EMOtion SEarch (MEMOSE), is largely based on the results of research regarding emotive music pieces, images and videos. In order to index both evoked and depicted emotions in these three media types and to make them searchable, we work with a controlled vocabulary, slide controls to adjust the emotions’ intensities, and broad folksonomies to identify and separate the correct resource-specific emotions. This separation of so-called power tags is based on a tag distribution which follows either an inverse power law (only one emotion was recognized) or an inverse-logistical shape (two or three emotions were recognized). Both distributions are well known in information science. MEMOSE consists of a tool for tagging basic emotions with the help of slide controls, a processing device to separate power tags, a retrieval component consisting of a search interface (for any topic in combination with one or more emotions) and a results screen. The latter shows two separately ranked lists of items for each media type (depicted and felt emotions), displaying thumbnails of resources, ranked by the mean values of intensity. In the evaluation of the MEMOSE prototype, study participants described our EmIR system as an enjoyable Web 2.0 service. |
| first_indexed | 2024-04-12T23:34:34Z |
| format | Article |
| id | doaj.art-2d3713da64504fa4ae0b335673572099 |
| institution | Directory Open Access Journal |
| issn | 2078-2489 |
| language | English |
| last_indexed | 2024-04-12T23:34:34Z |
| publishDate | 2011-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Information |
| spelling | doaj.art-2d3713da64504fa4ae0b3356735720992022-12-22T03:12:11ZengMDPI AGInformation2078-24892011-03-012121724610.3390/info2010217Finding Emotional-Laden Resources on the World Wide WebDiane Rasmussen NealStefanie SchmidtTobias SiebenlistWolfgang G. StockKathrin KnautzSome content in multimedia resources can depict or evoke certain emotions in users. The aim of Emotional Information Retrieval (EmIR) and of our research is to identify knowledge about emotional-laden documents and to use these findings in a new kind of World Wide Web information service that allows users to search and browse by emotion. Our prototype, called Media EMOtion SEarch (MEMOSE), is largely based on the results of research regarding emotive music pieces, images and videos. In order to index both evoked and depicted emotions in these three media types and to make them searchable, we work with a controlled vocabulary, slide controls to adjust the emotions’ intensities, and broad folksonomies to identify and separate the correct resource-specific emotions. This separation of so-called power tags is based on a tag distribution which follows either an inverse power law (only one emotion was recognized) or an inverse-logistical shape (two or three emotions were recognized). Both distributions are well known in information science. MEMOSE consists of a tool for tagging basic emotions with the help of slide controls, a processing device to separate power tags, a retrieval component consisting of a search interface (for any topic in combination with one or more emotions) and a results screen. The latter shows two separately ranked lists of items for each media type (depicted and felt emotions), displaying thumbnails of resources, ranked by the mean values of intensity. In the evaluation of the MEMOSE prototype, study participants described our EmIR system as an enjoyable Web 2.0 service.http://www.mdpi.com/2078-2489/2/1/217/emotional information retrievalindexing, retrievalcontent-based information retrievalbasic emotionconcept-based information retrievalimagevideomusictagging, scroll barMedia EMOtion SearchMEMOSE |
| spellingShingle | Diane Rasmussen Neal Stefanie Schmidt Tobias Siebenlist Wolfgang G. Stock Kathrin Knautz Finding Emotional-Laden Resources on the World Wide Web Information emotional information retrieval indexing, retrieval content-based information retrieval basic emotion concept-based information retrieval image video music tagging, scroll bar Media EMOtion Search MEMOSE |
| title | Finding Emotional-Laden Resources on the World Wide Web |
| title_full | Finding Emotional-Laden Resources on the World Wide Web |
| title_fullStr | Finding Emotional-Laden Resources on the World Wide Web |
| title_full_unstemmed | Finding Emotional-Laden Resources on the World Wide Web |
| title_short | Finding Emotional-Laden Resources on the World Wide Web |
| title_sort | finding emotional laden resources on the world wide web |
| topic | emotional information retrieval indexing, retrieval content-based information retrieval basic emotion concept-based information retrieval image video music tagging, scroll bar Media EMOtion Search MEMOSE |
| url | http://www.mdpi.com/2078-2489/2/1/217/ |
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