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Affect and Domain-Specific Components of the Self in Social Media.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Affect and Domain-Specific Components of the Self in Social Media./
Author:	Beasley, Dustin Asaf.
Description:	1 online resource (146 pages)
Notes:	Source: Dissertation Abstracts International, Volume: 79-04(E), Section: B.
Contained By:	Dissertation Abstracts International79-04B(E).
Subject:	Social psychology. -
Online resource:	click for full text (PQDT)
ISBN:	9780355354157

Affect and Domain-Specific Components of the Self in Social Media.
Beasley, Dustin Asaf.

Affect and Domain-Specific Components of the Self in Social Media. - 1 online resource (146 pages)

Source: Dissertation Abstracts International, Volume: 79-04(E), Section: B.

Thesis (Ph.D.)

Includes bibliographical references

Many are optimistic about how much we can infer about people from social media. On platforms like Facebook and Twitter, researchers have claimed to predict aspects of people's personality with high degrees of accuracy and to have captured complex psychological dynamics, like emotion contagion. Most of the work to date, however, has suffered from potentially serious methodological issues and provides little in the way of a) sound tests of psychological theory in the domain of social media or b) the creation of new psychological theory. Deeper considerations of the validity of measures and the general meaning of the features used to make predictions are often overlooked.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9780355354157Subjects--Topical Terms:

554804
Social psychology.
Index Terms--Genre/Form:

554714
Electronic books.

Affect and Domain-Specific Components of the Self in Social Media.
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100 1 $a Beasley, Dustin Asaf. $3 1180936
245 1 0 $a Affect and Domain-Specific Components of the Self in Social Media.
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300 $a 1 online resource (146 pages)
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500 $a Source: Dissertation Abstracts International, Volume: 79-04(E), Section: B.
500 $a Adviser: Eliot R. Smith.
502 $a Thesis (Ph.D.) $c Indiana University $d 2017.
504 $a Includes bibliographical references
520 $a Many are optimistic about how much we can infer about people from social media. On platforms like Facebook and Twitter, researchers have claimed to predict aspects of people's personality with high degrees of accuracy and to have captured complex psychological dynamics, like emotion contagion. Most of the work to date, however, has suffered from potentially serious methodological issues and provides little in the way of a) sound tests of psychological theory in the domain of social media or b) the creation of new psychological theory. Deeper considerations of the validity of measures and the general meaning of the features used to make predictions are often overlooked.
520 $a This dissertation explores the promises and challenges of inferring psychological constructs in social media. The first section examines the relationship between people's reported tendencies to feel positive and negative affect and the content of their posts on Facebook and Twitter. On a sample of nearly 800 social media users, I find little evidence for the widespread assumption that the frequencies of positive (e.g. 'happy', 'excited') and negative (e.g. 'sad', 'angry') words people use in their tweets and Facebook status updates meaningfully predicts their emotional state. The second section focuses on prediction of self-esteem connected to certain domains (e.g. academic performance) and political ideology using Twitter and Facebook data. Throughout the dissertation I address how we may improve practices in social media studies to better inform psychological theory, generate more reproducible results, and better compare findings across samples.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Social psychology. $3 554804
650 4 $a Psychology. $3 555998
650 4 $a Web studies. $3 1148502
655 7 $a Electronic books. $2 local $3 554714
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710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a Indiana University. $b Psychological & Brain Sciences. $3 1180937
773 0 $t Dissertation Abstracts International $g 79-04B(E).
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10634812 $z click for full text (PQDT)