Diurnal variations of psychometric indicators in Twitter content.
The psychological state of a person is characterised by cognitive and emotional variables which can be inferred by psychometric methods. Using the word lists from the Linguistic Inquiry and Word Count, designed to infer a range of psychological states from the word usage of a person, we studied temp...
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| Language: | English |
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Public Library of Science (PLoS)
2018-01-01
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| Series: | PLoS ONE |
| Online Access: | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0197002&type=printable |
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| author | Fabon Dzogang Stafford Lightman Nello Cristianini |
| author_facet | Fabon Dzogang Stafford Lightman Nello Cristianini |
| author_sort | Fabon Dzogang |
| collection | DOAJ |
| description | The psychological state of a person is characterised by cognitive and emotional variables which can be inferred by psychometric methods. Using the word lists from the Linguistic Inquiry and Word Count, designed to infer a range of psychological states from the word usage of a person, we studied temporal changes in the average expression of psychological traits in the general population. We sampled the contents of Twitter in the United Kingdom at hourly intervals for a period of four years, revealing a strong diurnal rhythm in most of the psychometric variables, and finding that two independent factors can explain 85% of the variance across their 24-h profiles. The first has peak expression time starting at 5am/6am, it correlates with measures of analytical thinking, with the language of drive (e.g power, and achievement), and personal concerns. It is anticorrelated with the language of negative affect and social concerns. The second factor has peak expression time starting at 3am/4am, it correlates with the language of existential concerns, and anticorrelates with expression of positive emotions. Overall, we see strong evidence that our language changes dramatically between night and day, reflecting changes in our concerns and underlying cognitive and emotional processes. These shifts occur at times associated with major changes in neural activity and hormonal levels. |
| format | Article |
| id | doaj-art-23e4bbc3b1b84a0cb1a4fc8187567708 |
| institution | DOAJ |
| issn | 1932-6203 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-23e4bbc3b1b84a0cb1a4fc81875677082025-08-20T02:46:01ZengPublic Library of Science (PLoS)PLoS ONE1932-62032018-01-01136e019700210.1371/journal.pone.0197002Diurnal variations of psychometric indicators in Twitter content.Fabon DzogangStafford LightmanNello CristianiniThe psychological state of a person is characterised by cognitive and emotional variables which can be inferred by psychometric methods. Using the word lists from the Linguistic Inquiry and Word Count, designed to infer a range of psychological states from the word usage of a person, we studied temporal changes in the average expression of psychological traits in the general population. We sampled the contents of Twitter in the United Kingdom at hourly intervals for a period of four years, revealing a strong diurnal rhythm in most of the psychometric variables, and finding that two independent factors can explain 85% of the variance across their 24-h profiles. The first has peak expression time starting at 5am/6am, it correlates with measures of analytical thinking, with the language of drive (e.g power, and achievement), and personal concerns. It is anticorrelated with the language of negative affect and social concerns. The second factor has peak expression time starting at 3am/4am, it correlates with the language of existential concerns, and anticorrelates with expression of positive emotions. Overall, we see strong evidence that our language changes dramatically between night and day, reflecting changes in our concerns and underlying cognitive and emotional processes. These shifts occur at times associated with major changes in neural activity and hormonal levels.https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0197002&type=printable |
| spellingShingle | Fabon Dzogang Stafford Lightman Nello Cristianini Diurnal variations of psychometric indicators in Twitter content. PLoS ONE |
| title | Diurnal variations of psychometric indicators in Twitter content. |
| title_full | Diurnal variations of psychometric indicators in Twitter content. |
| title_fullStr | Diurnal variations of psychometric indicators in Twitter content. |
| title_full_unstemmed | Diurnal variations of psychometric indicators in Twitter content. |
| title_short | Diurnal variations of psychometric indicators in Twitter content. |
| title_sort | diurnal variations of psychometric indicators in twitter content |
| url | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0197002&type=printable |
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