LitCovid-sentences  

PMC:7143846 / 6803-9107 JSONTXT 10 Projects

Annnotations TAB TSV DIC JSON TextAE

Id Subject Object Predicate Lexical cue
T51 0-4 Sentence denotes 2.2.
T52 5-55 Sentence denotes Measurement of Psychological Traits and Procedures
T53 56-309 Sentence denotes In this study, we used Online Ecological Recognition (OER) [20], which referred to the automatic recognition of psychological profile (e.g., anxiety, well-being, etc.) by using predictive models [17,20,21] based on ecological behavioral data from Weibo.
T54 310-574 Sentence denotes We employed Text Mind system developed by the Computational Cyber Psychology Laboratory at the Institute of Psychology, Chinese Academy of Sciences to extract content features [22], including Chinese word segmentation tool [17], and psychoanalytic dictionary [23].
T55 575-905 Sentence denotes We used the Chinese word segmentation tool to divide users’ original microblog content into words/phrases with linguistic annotations, such as verbs, nouns, adverbials, and objects [24], and then extracted psychologically meaningful categories through the simplified Chinese LIWC (Language Inquiry and Word Count) dictionary [23].
T56 906-975 Sentence denotes These lexical features were data sources for word frequency analysis.
T57 976-1154 Sentence denotes After feature extraction, we used the psychological prediction model [25] obtained from the preliminary training to predict the psychological profile of these active Weibo users.
T58 1155-1446 Sentence denotes These predictive models are tools developed for online psychology research based on big data and deep learning technologies, including emotional indicators (anxiety, depression, indignation, and Oxford happiness), cognitive indicators (social risk judgment and life satisfaction), and so on.
T59 1447-1541 Sentence denotes Figure 1 portrays the procedure from feature extraction to psychological indicator prediction.
T60 1542-1630 Sentence denotes All the prediction models have reached a moderate correlation with questionnaire scores.
T61 1631-1712 Sentence denotes The feasibility of predictive models has been repeatedly demonstrated [26,27,28].
T62 1713-1978 Sentence denotes We calculated word frequency, scores of negative emotional indicators (i.e., anxiety, depression, and indignation), positive emotional indicators (i.e., Oxford happiness), and cognitive indicators (i.e., social risk and life satisfaction) of the collected messages.
T63 1979-2304 Sentence denotes We then compared the differences of psychological characteristics before and after the declaration of outbreak of COVID-19 on 20 January, 2020 through the paired sample t-test by using SPSS (Statistical Product and Service Solutions) 22, which is published by IBM (International Business Machines Corporation), New York, USA.