Data-Driven Content Analysis of Social Media
2015 ◽
Vol 659
(1)
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pp. 78-94
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Researchers have long measured people’s thoughts, feelings, and personalities using carefully designed survey questions, which are often given to a relatively small number of volunteers. The proliferation of social media, such as Twitter and Facebook, offers alternative measurement approaches: automatic content coding at unprecedented scales and the statistical power to do open-vocabulary exploratory analysis. We describe a range of automatic and partially automatic content analysis techniques and illustrate how their use on social media generates insights into subjective well-being, health, gender differences, and personality.
2020 ◽
Vol 117
(19)
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pp. 10165-10171
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2015 ◽
Vol 116
(1)
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pp. 311-321
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2021 ◽
Vol 66
(1)
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pp. 5-36
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2016 ◽
Vol 5
(10)
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pp. 49-70
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