The Resource Identifying personality and topics of social media, Trinadha Rajeswari Muppala
Identifying personality and topics of social media, Trinadha Rajeswari Muppala
Resource Information
The item Identifying personality and topics of social media, Trinadha Rajeswari Muppala represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of Missouri-Kansas City Libraries.This item is available to borrow from all library branches.
Resource Information
The item Identifying personality and topics of social media, Trinadha Rajeswari Muppala represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of Missouri-Kansas City Libraries.
This item is available to borrow from all library branches.
- Summary
- Twitter and Facebook are the renowned social networking platforms where users post, share, interact and express to the world, their interests, personality, and behavioral information. User-created content on social media can be a source of truth, which is suitable to be consumed for the personality identification of social media users. Personality assessment using the Big 5 personality factor model benefits organizations in identifying potential professionals, future leaders, best-fit candidates for the role, and build effective teams. Also, the Big 5 personality factors help to understand depression symptoms among aged people in primary care. We had hypothesized that understanding the user personality of the social network would have significant benefits for topic modeling of different areas like news, towards understanding community interests, and topics. In this thesis, we will present a multi-label personality classification of the social media data and topic feature classification model based on the Big 5 model. We have built the Big 5 personality classification model using a Twitter dataset that has defined openness, conscientiousness, extraversion, agreeableness, and neuroticism. In this thesis, we (1) conduct personality detection using the Big 5 model, (2) extract the topics from Facebook and Twitter data based on each personality, (3) analyze the top essential topics, and (4) find the relation between topics and personalities. The personality would be useful to identify what kind of personality, which topics usually talk about in social media. Multi-label classification is done using Multinomial Naïve Bayes, Logistic Regression, Linear SVC. Topic Modeling is done based on LDA and KATE. Experimental results with Twitter and Facebook data demonstrate that the proposed model has achieved promising results
- Language
- eng
- Extent
- 1 online resource (40 pages)
- Note
-
- "A thesis in Computer Science."
- Advisor: Yugyung Lee
- Vita
- Contents
-
- Introduction
- Background and related work
- Proposed framework
- Results and evaluations
- Conclusion and future work
- Label
- Identifying personality and topics of social media
- Title
- Identifying personality and topics of social media
- Statement of responsibility
- Trinadha Rajeswari Muppala
- Language
- eng
- Summary
- Twitter and Facebook are the renowned social networking platforms where users post, share, interact and express to the world, their interests, personality, and behavioral information. User-created content on social media can be a source of truth, which is suitable to be consumed for the personality identification of social media users. Personality assessment using the Big 5 personality factor model benefits organizations in identifying potential professionals, future leaders, best-fit candidates for the role, and build effective teams. Also, the Big 5 personality factors help to understand depression symptoms among aged people in primary care. We had hypothesized that understanding the user personality of the social network would have significant benefits for topic modeling of different areas like news, towards understanding community interests, and topics. In this thesis, we will present a multi-label personality classification of the social media data and topic feature classification model based on the Big 5 model. We have built the Big 5 personality classification model using a Twitter dataset that has defined openness, conscientiousness, extraversion, agreeableness, and neuroticism. In this thesis, we (1) conduct personality detection using the Big 5 model, (2) extract the topics from Facebook and Twitter data based on each personality, (3) analyze the top essential topics, and (4) find the relation between topics and personalities. The personality would be useful to identify what kind of personality, which topics usually talk about in social media. Multi-label classification is done using Multinomial Naïve Bayes, Logistic Regression, Linear SVC. Topic Modeling is done based on LDA and KATE. Experimental results with Twitter and Facebook data demonstrate that the proposed model has achieved promising results
- Cataloging source
- UMK
- http://library.link/vocab/creatorName
- Muppala, Trinadha Rajeswari
- Degree
- M.S.
- Dissertation year
- 2019.
- Granting institution
- School of Computing and Engineering. University of Missouri-Kansas City,
- Illustrations
- illustrations
- Index
- no index present
- Literary form
- non fiction
- Nature of contents
-
- dictionaries
- bibliography
- theses
- http://library.link/vocab/relatedWorkOrContributorDate
- 1960-
- http://library.link/vocab/relatedWorkOrContributorName
- Lee, Yugyung
- http://library.link/vocab/subjectName
-
- Social media
- Personality assessment
- Machine learning
- Label
- Identifying personality and topics of social media, Trinadha Rajeswari Muppala
- Note
-
- "A thesis in Computer Science."
- Advisor: Yugyung Lee
- Vita
- Antecedent source
- not applicable
- Bibliography note
- Includes bibliographical references (pages 37-39)
- Carrier category
- online resource
- Carrier category code
-
- cr
- Carrier MARC source
- rdacarrier
- Color
- black and white
- Content category
- text
- Content type code
-
- txt
- Content type MARC source
- rdacontent
- Contents
- Introduction -- Background and related work -- Proposed framework -- Results and evaluations -- Conclusion and future work
- Control code
- 1137540119
- Dimensions
- unknown
- Extent
- 1 online resource (40 pages)
- File format
- one file format
- Form of item
- online
- Level of compression
- mixed
- Media category
- computer
- Media MARC source
- rdamedia
- Media type code
-
- c
- Other physical details
- illustrations.
- Quality assurance targets
- not applicable
- Specific material designation
- remote
- System control number
- (OCoLC)1137540119
- System details
-
- The full text of the thesis is available as an Adobe Acrobat .pdf file; Adobe Acrobat Reader required to view the file
- Mode of access: World Wide Web
- Label
- Identifying personality and topics of social media, Trinadha Rajeswari Muppala
- Note
-
- "A thesis in Computer Science."
- Advisor: Yugyung Lee
- Vita
- Antecedent source
- not applicable
- Bibliography note
- Includes bibliographical references (pages 37-39)
- Carrier category
- online resource
- Carrier category code
-
- cr
- Carrier MARC source
- rdacarrier
- Color
- black and white
- Content category
- text
- Content type code
-
- txt
- Content type MARC source
- rdacontent
- Contents
- Introduction -- Background and related work -- Proposed framework -- Results and evaluations -- Conclusion and future work
- Control code
- 1137540119
- Dimensions
- unknown
- Extent
- 1 online resource (40 pages)
- File format
- one file format
- Form of item
- online
- Level of compression
- mixed
- Media category
- computer
- Media MARC source
- rdamedia
- Media type code
-
- c
- Other physical details
- illustrations.
- Quality assurance targets
- not applicable
- Specific material designation
- remote
- System control number
- (OCoLC)1137540119
- System details
-
- The full text of the thesis is available as an Adobe Acrobat .pdf file; Adobe Acrobat Reader required to view the file
- Mode of access: World Wide Web
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<div class="citation" vocab="http://schema.org/"><i class="fa fa-external-link-square fa-fw"></i> Data from <span resource="http://link.library.umkc.edu/portal/Identifying-personality-and-topics-of-social/C7Lsy-VogOA/" typeof="Book http://bibfra.me/vocab/lite/Item"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.library.umkc.edu/portal/Identifying-personality-and-topics-of-social/C7Lsy-VogOA/">Identifying personality and topics of social media, Trinadha Rajeswari Muppala</a></span> - <span property="potentialAction" typeOf="OrganizeAction"><span property="agent" typeof="LibrarySystem http://library.link/vocab/LibrarySystem" resource="http://link.library.umkc.edu/"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.library.umkc.edu/">University of Missouri-Kansas City Libraries</a></span></span></span></span></div>
