Using social media activity to identify personality characteristics of Navy personnel
dc.contributor.advisor | Shing, Man-Tak | |
dc.contributor.advisor | Otani, Thomas | |
dc.contributor.author | Ward, Leslie | |
dc.date | Mar-16 | |
dc.date.accessioned | 2016-04-29T21:19:08Z | |
dc.date.available | 2016-04-29T21:19:08Z | |
dc.date.issued | 2016-03 | |
dc.identifier.uri | https://hdl.handle.net/10945/48492 | |
dc.description.abstract | This research explores the use of Twitter to determine if the personality characteristics of well-performing Navy personnel can be identified based on their Twitter use. Well-performing Navy personnel are identified by using the publicly-available Navy promotion lists and then those names were used to query Twitter in order to identify possible accounts belonging to these Sailors. Data from those Twitter accounts that could be positively identified as belonging to Navy personnel were then fed into textual analysis software and each user’s level of the personality traits in the Five Factor Model of personality was calculated based on the results previous research. These results and other data were also stored in a graph database in order to make the data easier to query. Although this research shows that it is possible to successfully calculate a user’s personality based on textual analysis of their Twitter activity, the primary conclusions of this research is that this method is insufficient to identify specific traits that make Navy personnel stand out on Twitter. | en_US |
dc.description.uri | http://archive.org/details/usingsocialmedia1094548492 | |
dc.publisher | Monterey, California: Naval Postgraduate School | en_US |
dc.rights | This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States. | en_US |
dc.title | Using social media activity to identify personality characteristics of Navy personnel | en_US |
dc.type | Thesis | en_US |
dc.contributor.department | Computer Science | |
dc.contributor.department | Computer Science | en_US |
dc.subject.author | en_US | |
dc.subject.author | personality | en_US |
dc.subject.author | Five Factor Model | en_US |
dc.subject.author | graph database | en_US |
dc.subject.author | textual analysis | en_US |
dc.subject.author | LIWC | en_US |
dc.description.service | Lieutenant, United States Navy | en_US |
etd.thesisdegree.name | Master of Science in Computer Science | en_US |
etd.thesisdegree.level | Masters | en_US |
etd.thesisdegree.discipline | Computer Science | en_US |
etd.thesisdegree.grantor | Naval Postgraduate School | en_US |
dc.description.distributionstatement | Approved for public release; distribution is unlimited. |
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