What Machines Understand about Personality Words after Reading the News
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Wright State University / OhioLINK
2014
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| Online Access: | http://rave.ohiolink.edu/etdc/view?acc_num=wright1404902086 |
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ndltd-OhioLink-oai-etd.ohiolink.edu-wright14049020862021-08-03T06:25:46Z What Machines Understand about Personality Words after Reading the News Moyer, Eric David Computer Science Psychology Personality Psychology Personality Modern Language skip-gram personality personality psychology vector space semantics lexical semantics natural language processing vector space lexical semantics word2vec distributed representations Vector-based lexical semantics is a powerful technique that still has many undiscovered applications. In this thesis I apply a vector-space lexical-semantic model newly developed by Mikolov et. al. trained on skip-grams to the lexical hypothesis in personality psychology. The method produces interpretable dimensions that are consistent across several sets of descriptive personality words. The dimensions include ones for conflict and positive and negative evaluation. However they are more descriptive of word usage semantics than of the characteristics of the thing described and thus do not include a recognizable component of the 5 factor model in their first 14 dimensions. They do include a component that seems to indicate the degree to which the word applies to people that could be useful in identifying personality words in English. 2014-12-15 English text Wright State University / OhioLINK http://rave.ohiolink.edu/etdc/view?acc_num=wright1404902086 http://rave.ohiolink.edu/etdc/view?acc_num=wright1404902086 unrestricted This thesis or dissertation is protected by copyright: some rights reserved. It is licensed for use under a Creative Commons license. Specific terms and permissions are available from this document's record in the OhioLINK ETD Center. |
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NDLTD |
| language |
English |
| sources |
NDLTD |
| topic |
Computer Science Psychology Personality Psychology Personality Modern Language skip-gram personality personality psychology vector space semantics lexical semantics natural language processing vector space lexical semantics word2vec distributed representations |
| spellingShingle |
Computer Science Psychology Personality Psychology Personality Modern Language skip-gram personality personality psychology vector space semantics lexical semantics natural language processing vector space lexical semantics word2vec distributed representations Moyer, Eric David What Machines Understand about Personality Words after Reading the News |
| author |
Moyer, Eric David |
| author_facet |
Moyer, Eric David |
| author_sort |
Moyer, Eric David |
| title |
What Machines Understand about Personality Words after Reading the News |
| title_short |
What Machines Understand about Personality Words after Reading the News |
| title_full |
What Machines Understand about Personality Words after Reading the News |
| title_fullStr |
What Machines Understand about Personality Words after Reading the News |
| title_full_unstemmed |
What Machines Understand about Personality Words after Reading the News |
| title_sort |
what machines understand about personality words after reading the news |
| publisher |
Wright State University / OhioLINK |
| publishDate |
2014 |
| url |
http://rave.ohiolink.edu/etdc/view?acc_num=wright1404902086 |
| work_keys_str_mv |
AT moyerericdavid whatmachinesunderstandaboutpersonalitywordsafterreadingthenews |
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