PMC:7143846 / 9109-11759 JSONTXT

{"project":"LitCovid-PubTator","denotations":[{"id":"105","span":{"begin":290,"end":293},"obj":"Gene"},{"id":"110","span":{"begin":1158,"end":1164},"obj":"Species"},{"id":"111","span":{"begin":739,"end":746},"obj":"Disease"},{"id":"112","span":{"begin":851,"end":859},"obj":"Disease"},{"id":"113","span":{"begin":1042,"end":1047},"obj":"Disease"},{"id":"116","span":{"begin":1349,"end":1356},"obj":"Disease"},{"id":"117","span":{"begin":1552,"end":1557},"obj":"Disease"},{"id":"120","span":{"begin":2014,"end":2021},"obj":"Disease"},{"id":"121","span":{"begin":2057,"end":2067},"obj":"Disease"}],"attributes":[{"id":"A105","pred":"tao:has_database_id","subj":"105","obj":"Gene:5973"},{"id":"A110","pred":"tao:has_database_id","subj":"110","obj":"Tax:9606"},{"id":"A111","pred":"tao:has_database_id","subj":"111","obj":"MESH:D001007"},{"id":"A112","pred":"tao:has_database_id","subj":"112","obj":"MESH:D007319"},{"id":"A113","pred":"tao:has_database_id","subj":"113","obj":"MESH:D003643"},{"id":"A116","pred":"tao:has_database_id","subj":"116","obj":"MESH:D001007"},{"id":"A117","pred":"tao:has_database_id","subj":"117","obj":"MESH:D003643"},{"id":"A120","pred":"tao:has_database_id","subj":"120","obj":"MESH:D001007"},{"id":"A121","pred":"tao:has_database_id","subj":"121","obj":"MESH:D000275"}],"namespaces":[{"prefix":"Tax","uri":"https://www.ncbi.nlm.nih.gov/taxonomy/"},{"prefix":"MESH","uri":"https://id.nlm.nih.gov/mesh/"},{"prefix":"Gene","uri":"https://www.ncbi.nlm.nih.gov/gene/"},{"prefix":"CVCL","uri":"https://web.expasy.org/cellosaurus/CVCL_"}],"text":"3. Results\n\n3.1. Demographics\nAmong 17,865 active Weibo users, 25.23% were males and 77.95% were from Eastern China, which is considered the richest region in China. Ages of users who registered their birth date in their profile (n = 4156, 23.26%) ranged from 8 to 56 years with the median age of 33 years. The demographic profile is depicted in Table 1.\n\n3.2. Linguistic Difference\nIn this study, we compare the LIWC categories between the week before (T-before) and after (T-after) 20 January, shown in Table 2. It contains two types of LIWC categories: words of emotions and words of concerns. Words of emotions include positive emotion (e.g., faith, contentment, and blessing), negative emotion (e.g., worry, suspicion, and jealousy), anxiety (e.g., upset, nervous, and crazy), and anger (e.g., complaint). Words of concerns include health (e.g., insomnia, doctor, and exercise), leisure (e.g., cooking, chatting, and movies), family (e.g., family and house), friend (e.g., companion and guest), money (e.g., bills, cash, and borrowing), death (e.g., burial, killing, and funeral), and religion (e.g., church, mosque, and temple), which can reflect what people are paying attention to.\nAfter 20 January, the number of words increased in positive emotion (t (17,747) = −24.411, p \u003c 0.001), negative emotion (t (17,747) = −15.273, p \u003c 0.001), and anxiety (t (17,747) = −15.294, p \u003c 0.001). Word frequency significantly increased in the category “concerns,” including health (t (17,747) = −72.392, p \u003c 0.05), family (t (17,747) = −12.571, p \u003c 0.001), death (t (17,747) = −6.707, p \u003c 0.001), and religion (t (17,747) = −13.816, p \u003c 0.001), but decreased in leisure (t (17,747) = 21.963, p \u003c 0.001) and friend (t (17,747) = 6.202, p \u003c 0.001).\n\n3.3. Emotional Indicators\nResults indicate significant differences of emotional indicators between T-before (13–19 January, 2020) and T-after (20–26 January, 2020), as shown in Table 3. After 20 January, negative emotional indicators of psychological traits increased in anxiety (t (17,747) = −35.962, p \u003c 0.001), depression (t (17,747) = −10.717, p \u003c 0.001), and indignation (t (17,747) = 5.500, p \u003c 0.001), while positive emotional indicators of psychological traits decreased in Oxford happiness (t (17,747) = 3.120, p \u003c 0.01).\n\n3.4. Cognitive Indicators\nWe found significant differences in cognitive indicators between T-before (13–19 January, 2020) and T-after (20–26 January, 2020), as shown in Table 4. After 20 January, cognitive indicators of psychological traits increased in social risk judgement (t (17,747) = 3.120, p \u003c 0.01), but decreased in life satisfaction (t (17,747) = 5.500, p \u003c 0.001)."}

{"project":"LitCovid-PD-FMA-UBERON","denotations":[{"id":"T6","span":{"begin":1126,"end":1132},"obj":"Body_part"}],"attributes":[{"id":"A6","pred":"fma_id","subj":"T6","obj":"http://purl.org/sig/ont/fma/fma320470"}],"text":"3. Results\n\n3.1. Demographics\nAmong 17,865 active Weibo users, 25.23% were males and 77.95% were from Eastern China, which is considered the richest region in China. Ages of users who registered their birth date in their profile (n = 4156, 23.26%) ranged from 8 to 56 years with the median age of 33 years. The demographic profile is depicted in Table 1.\n\n3.2. Linguistic Difference\nIn this study, we compare the LIWC categories between the week before (T-before) and after (T-after) 20 January, shown in Table 2. It contains two types of LIWC categories: words of emotions and words of concerns. Words of emotions include positive emotion (e.g., faith, contentment, and blessing), negative emotion (e.g., worry, suspicion, and jealousy), anxiety (e.g., upset, nervous, and crazy), and anger (e.g., complaint). Words of concerns include health (e.g., insomnia, doctor, and exercise), leisure (e.g., cooking, chatting, and movies), family (e.g., family and house), friend (e.g., companion and guest), money (e.g., bills, cash, and borrowing), death (e.g., burial, killing, and funeral), and religion (e.g., church, mosque, and temple), which can reflect what people are paying attention to.\nAfter 20 January, the number of words increased in positive emotion (t (17,747) = −24.411, p \u003c 0.001), negative emotion (t (17,747) = −15.273, p \u003c 0.001), and anxiety (t (17,747) = −15.294, p \u003c 0.001). Word frequency significantly increased in the category “concerns,” including health (t (17,747) = −72.392, p \u003c 0.05), family (t (17,747) = −12.571, p \u003c 0.001), death (t (17,747) = −6.707, p \u003c 0.001), and religion (t (17,747) = −13.816, p \u003c 0.001), but decreased in leisure (t (17,747) = 21.963, p \u003c 0.001) and friend (t (17,747) = 6.202, p \u003c 0.001).\n\n3.3. Emotional Indicators\nResults indicate significant differences of emotional indicators between T-before (13–19 January, 2020) and T-after (20–26 January, 2020), as shown in Table 3. After 20 January, negative emotional indicators of psychological traits increased in anxiety (t (17,747) = −35.962, p \u003c 0.001), depression (t (17,747) = −10.717, p \u003c 0.001), and indignation (t (17,747) = 5.500, p \u003c 0.001), while positive emotional indicators of psychological traits decreased in Oxford happiness (t (17,747) = 3.120, p \u003c 0.01).\n\n3.4. Cognitive Indicators\nWe found significant differences in cognitive indicators between T-before (13–19 January, 2020) and T-after (20–26 January, 2020), as shown in Table 4. After 20 January, cognitive indicators of psychological traits increased in social risk judgement (t (17,747) = 3.120, p \u003c 0.01), but decreased in life satisfaction (t (17,747) = 5.500, p \u003c 0.001)."}

{"project":"LitCovid-PD-MONDO","denotations":[{"id":"T41","span":{"begin":739,"end":746},"obj":"Disease"},{"id":"T43","span":{"begin":851,"end":859},"obj":"Disease"},{"id":"T44","span":{"begin":1349,"end":1356},"obj":"Disease"},{"id":"T46","span":{"begin":2014,"end":2021},"obj":"Disease"},{"id":"T48","span":{"begin":2057,"end":2067},"obj":"Disease"}],"attributes":[{"id":"A41","pred":"mondo_id","subj":"T41","obj":"http://purl.obolibrary.org/obo/MONDO_0005618"},{"id":"A42","pred":"mondo_id","subj":"T41","obj":"http://purl.obolibrary.org/obo/MONDO_0011918"},{"id":"A43","pred":"mondo_id","subj":"T43","obj":"http://purl.obolibrary.org/obo/MONDO_0013600"},{"id":"A44","pred":"mondo_id","subj":"T44","obj":"http://purl.obolibrary.org/obo/MONDO_0005618"},{"id":"A45","pred":"mondo_id","subj":"T44","obj":"http://purl.obolibrary.org/obo/MONDO_0011918"},{"id":"A46","pred":"mondo_id","subj":"T46","obj":"http://purl.obolibrary.org/obo/MONDO_0005618"},{"id":"A47","pred":"mondo_id","subj":"T46","obj":"http://purl.obolibrary.org/obo/MONDO_0011918"},{"id":"A48","pred":"mondo_id","subj":"T48","obj":"http://purl.obolibrary.org/obo/MONDO_0002050"}],"text":"3. Results\n\n3.1. Demographics\nAmong 17,865 active Weibo users, 25.23% were males and 77.95% were from Eastern China, which is considered the richest region in China. Ages of users who registered their birth date in their profile (n = 4156, 23.26%) ranged from 8 to 56 years with the median age of 33 years. The demographic profile is depicted in Table 1.\n\n3.2. Linguistic Difference\nIn this study, we compare the LIWC categories between the week before (T-before) and after (T-after) 20 January, shown in Table 2. It contains two types of LIWC categories: words of emotions and words of concerns. Words of emotions include positive emotion (e.g., faith, contentment, and blessing), negative emotion (e.g., worry, suspicion, and jealousy), anxiety (e.g., upset, nervous, and crazy), and anger (e.g., complaint). Words of concerns include health (e.g., insomnia, doctor, and exercise), leisure (e.g., cooking, chatting, and movies), family (e.g., family and house), friend (e.g., companion and guest), money (e.g., bills, cash, and borrowing), death (e.g., burial, killing, and funeral), and religion (e.g., church, mosque, and temple), which can reflect what people are paying attention to.\nAfter 20 January, the number of words increased in positive emotion (t (17,747) = −24.411, p \u003c 0.001), negative emotion (t (17,747) = −15.273, p \u003c 0.001), and anxiety (t (17,747) = −15.294, p \u003c 0.001). Word frequency significantly increased in the category “concerns,” including health (t (17,747) = −72.392, p \u003c 0.05), family (t (17,747) = −12.571, p \u003c 0.001), death (t (17,747) = −6.707, p \u003c 0.001), and religion (t (17,747) = −13.816, p \u003c 0.001), but decreased in leisure (t (17,747) = 21.963, p \u003c 0.001) and friend (t (17,747) = 6.202, p \u003c 0.001).\n\n3.3. Emotional Indicators\nResults indicate significant differences of emotional indicators between T-before (13–19 January, 2020) and T-after (20–26 January, 2020), as shown in Table 3. After 20 January, negative emotional indicators of psychological traits increased in anxiety (t (17,747) = −35.962, p \u003c 0.001), depression (t (17,747) = −10.717, p \u003c 0.001), and indignation (t (17,747) = 5.500, p \u003c 0.001), while positive emotional indicators of psychological traits decreased in Oxford happiness (t (17,747) = 3.120, p \u003c 0.01).\n\n3.4. Cognitive Indicators\nWe found significant differences in cognitive indicators between T-before (13–19 January, 2020) and T-after (20–26 January, 2020), as shown in Table 4. After 20 January, cognitive indicators of psychological traits increased in social risk judgement (t (17,747) = 3.120, p \u003c 0.01), but decreased in life satisfaction (t (17,747) = 5.500, p \u003c 0.001)."}

{"project":"LitCovid-PD-CLO","denotations":[{"id":"T42","span":{"begin":43,"end":49},"obj":"http://purl.obolibrary.org/obo/CLO_0001658"},{"id":"T43","span":{"begin":75,"end":80},"obj":"http://purl.obolibrary.org/obo/UBERON_0003101"},{"id":"T44","span":{"begin":75,"end":80},"obj":"http://www.ebi.ac.uk/efo/EFO_0000970"}],"text":"3. Results\n\n3.1. Demographics\nAmong 17,865 active Weibo users, 25.23% were males and 77.95% were from Eastern China, which is considered the richest region in China. Ages of users who registered their birth date in their profile (n = 4156, 23.26%) ranged from 8 to 56 years with the median age of 33 years. The demographic profile is depicted in Table 1.\n\n3.2. Linguistic Difference\nIn this study, we compare the LIWC categories between the week before (T-before) and after (T-after) 20 January, shown in Table 2. It contains two types of LIWC categories: words of emotions and words of concerns. Words of emotions include positive emotion (e.g., faith, contentment, and blessing), negative emotion (e.g., worry, suspicion, and jealousy), anxiety (e.g., upset, nervous, and crazy), and anger (e.g., complaint). Words of concerns include health (e.g., insomnia, doctor, and exercise), leisure (e.g., cooking, chatting, and movies), family (e.g., family and house), friend (e.g., companion and guest), money (e.g., bills, cash, and borrowing), death (e.g., burial, killing, and funeral), and religion (e.g., church, mosque, and temple), which can reflect what people are paying attention to.\nAfter 20 January, the number of words increased in positive emotion (t (17,747) = −24.411, p \u003c 0.001), negative emotion (t (17,747) = −15.273, p \u003c 0.001), and anxiety (t (17,747) = −15.294, p \u003c 0.001). Word frequency significantly increased in the category “concerns,” including health (t (17,747) = −72.392, p \u003c 0.05), family (t (17,747) = −12.571, p \u003c 0.001), death (t (17,747) = −6.707, p \u003c 0.001), and religion (t (17,747) = −13.816, p \u003c 0.001), but decreased in leisure (t (17,747) = 21.963, p \u003c 0.001) and friend (t (17,747) = 6.202, p \u003c 0.001).\n\n3.3. Emotional Indicators\nResults indicate significant differences of emotional indicators between T-before (13–19 January, 2020) and T-after (20–26 January, 2020), as shown in Table 3. After 20 January, negative emotional indicators of psychological traits increased in anxiety (t (17,747) = −35.962, p \u003c 0.001), depression (t (17,747) = −10.717, p \u003c 0.001), and indignation (t (17,747) = 5.500, p \u003c 0.001), while positive emotional indicators of psychological traits decreased in Oxford happiness (t (17,747) = 3.120, p \u003c 0.01).\n\n3.4. Cognitive Indicators\nWe found significant differences in cognitive indicators between T-before (13–19 January, 2020) and T-after (20–26 January, 2020), as shown in Table 4. After 20 January, cognitive indicators of psychological traits increased in social risk judgement (t (17,747) = 3.120, p \u003c 0.01), but decreased in life satisfaction (t (17,747) = 5.500, p \u003c 0.001)."}

{"project":"LitCovid-PD-HP","denotations":[{"id":"T12","span":{"begin":739,"end":746},"obj":"Phenotype"},{"id":"T13","span":{"begin":851,"end":859},"obj":"Phenotype"},{"id":"T14","span":{"begin":1349,"end":1356},"obj":"Phenotype"},{"id":"T15","span":{"begin":2014,"end":2021},"obj":"Phenotype"},{"id":"T16","span":{"begin":2057,"end":2067},"obj":"Phenotype"}],"attributes":[{"id":"A12","pred":"hp_id","subj":"T12","obj":"http://purl.obolibrary.org/obo/HP_0000739"},{"id":"A13","pred":"hp_id","subj":"T13","obj":"http://purl.obolibrary.org/obo/HP_0100785"},{"id":"A14","pred":"hp_id","subj":"T14","obj":"http://purl.obolibrary.org/obo/HP_0000739"},{"id":"A15","pred":"hp_id","subj":"T15","obj":"http://purl.obolibrary.org/obo/HP_0000739"},{"id":"A16","pred":"hp_id","subj":"T16","obj":"http://purl.obolibrary.org/obo/HP_0000716"}],"text":"3. Results\n\n3.1. Demographics\nAmong 17,865 active Weibo users, 25.23% were males and 77.95% were from Eastern China, which is considered the richest region in China. Ages of users who registered their birth date in their profile (n = 4156, 23.26%) ranged from 8 to 56 years with the median age of 33 years. The demographic profile is depicted in Table 1.\n\n3.2. Linguistic Difference\nIn this study, we compare the LIWC categories between the week before (T-before) and after (T-after) 20 January, shown in Table 2. It contains two types of LIWC categories: words of emotions and words of concerns. Words of emotions include positive emotion (e.g., faith, contentment, and blessing), negative emotion (e.g., worry, suspicion, and jealousy), anxiety (e.g., upset, nervous, and crazy), and anger (e.g., complaint). Words of concerns include health (e.g., insomnia, doctor, and exercise), leisure (e.g., cooking, chatting, and movies), family (e.g., family and house), friend (e.g., companion and guest), money (e.g., bills, cash, and borrowing), death (e.g., burial, killing, and funeral), and religion (e.g., church, mosque, and temple), which can reflect what people are paying attention to.\nAfter 20 January, the number of words increased in positive emotion (t (17,747) = −24.411, p \u003c 0.001), negative emotion (t (17,747) = −15.273, p \u003c 0.001), and anxiety (t (17,747) = −15.294, p \u003c 0.001). Word frequency significantly increased in the category “concerns,” including health (t (17,747) = −72.392, p \u003c 0.05), family (t (17,747) = −12.571, p \u003c 0.001), death (t (17,747) = −6.707, p \u003c 0.001), and religion (t (17,747) = −13.816, p \u003c 0.001), but decreased in leisure (t (17,747) = 21.963, p \u003c 0.001) and friend (t (17,747) = 6.202, p \u003c 0.001).\n\n3.3. Emotional Indicators\nResults indicate significant differences of emotional indicators between T-before (13–19 January, 2020) and T-after (20–26 January, 2020), as shown in Table 3. After 20 January, negative emotional indicators of psychological traits increased in anxiety (t (17,747) = −35.962, p \u003c 0.001), depression (t (17,747) = −10.717, p \u003c 0.001), and indignation (t (17,747) = 5.500, p \u003c 0.001), while positive emotional indicators of psychological traits decreased in Oxford happiness (t (17,747) = 3.120, p \u003c 0.01).\n\n3.4. Cognitive Indicators\nWe found significant differences in cognitive indicators between T-before (13–19 January, 2020) and T-after (20–26 January, 2020), as shown in Table 4. After 20 January, cognitive indicators of psychological traits increased in social risk judgement (t (17,747) = 3.120, p \u003c 0.01), but decreased in life satisfaction (t (17,747) = 5.500, p \u003c 0.001)."}

{"project":"LitCovid-sentences","denotations":[{"id":"T64","span":{"begin":0,"end":2},"obj":"Sentence"},{"id":"T65","span":{"begin":3,"end":10},"obj":"Sentence"},{"id":"T66","span":{"begin":12,"end":16},"obj":"Sentence"},{"id":"T67","span":{"begin":17,"end":29},"obj":"Sentence"},{"id":"T68","span":{"begin":30,"end":165},"obj":"Sentence"},{"id":"T69","span":{"begin":166,"end":306},"obj":"Sentence"},{"id":"T70","span":{"begin":307,"end":354},"obj":"Sentence"},{"id":"T71","span":{"begin":356,"end":360},"obj":"Sentence"},{"id":"T72","span":{"begin":361,"end":382},"obj":"Sentence"},{"id":"T73","span":{"begin":383,"end":513},"obj":"Sentence"},{"id":"T74","span":{"begin":514,"end":596},"obj":"Sentence"},{"id":"T75","span":{"begin":597,"end":810},"obj":"Sentence"},{"id":"T76","span":{"begin":811,"end":1189},"obj":"Sentence"},{"id":"T77","span":{"begin":1190,"end":1391},"obj":"Sentence"},{"id":"T78","span":{"begin":1392,"end":1741},"obj":"Sentence"},{"id":"T79","span":{"begin":1743,"end":1747},"obj":"Sentence"},{"id":"T80","span":{"begin":1748,"end":1768},"obj":"Sentence"},{"id":"T81","span":{"begin":1769,"end":1928},"obj":"Sentence"},{"id":"T82","span":{"begin":1929,"end":2273},"obj":"Sentence"},{"id":"T83","span":{"begin":2275,"end":2279},"obj":"Sentence"},{"id":"T84","span":{"begin":2280,"end":2300},"obj":"Sentence"},{"id":"T85","span":{"begin":2301,"end":2452},"obj":"Sentence"},{"id":"T86","span":{"begin":2453,"end":2650},"obj":"Sentence"}],"namespaces":[{"prefix":"_base","uri":"http://pubannotation.org/ontology/tao.owl#"}],"text":"3. Results\n\n3.1. Demographics\nAmong 17,865 active Weibo users, 25.23% were males and 77.95% were from Eastern China, which is considered the richest region in China. Ages of users who registered their birth date in their profile (n = 4156, 23.26%) ranged from 8 to 56 years with the median age of 33 years. The demographic profile is depicted in Table 1.\n\n3.2. Linguistic Difference\nIn this study, we compare the LIWC categories between the week before (T-before) and after (T-after) 20 January, shown in Table 2. It contains two types of LIWC categories: words of emotions and words of concerns. Words of emotions include positive emotion (e.g., faith, contentment, and blessing), negative emotion (e.g., worry, suspicion, and jealousy), anxiety (e.g., upset, nervous, and crazy), and anger (e.g., complaint). Words of concerns include health (e.g., insomnia, doctor, and exercise), leisure (e.g., cooking, chatting, and movies), family (e.g., family and house), friend (e.g., companion and guest), money (e.g., bills, cash, and borrowing), death (e.g., burial, killing, and funeral), and religion (e.g., church, mosque, and temple), which can reflect what people are paying attention to.\nAfter 20 January, the number of words increased in positive emotion (t (17,747) = −24.411, p \u003c 0.001), negative emotion (t (17,747) = −15.273, p \u003c 0.001), and anxiety (t (17,747) = −15.294, p \u003c 0.001). Word frequency significantly increased in the category “concerns,” including health (t (17,747) = −72.392, p \u003c 0.05), family (t (17,747) = −12.571, p \u003c 0.001), death (t (17,747) = −6.707, p \u003c 0.001), and religion (t (17,747) = −13.816, p \u003c 0.001), but decreased in leisure (t (17,747) = 21.963, p \u003c 0.001) and friend (t (17,747) = 6.202, p \u003c 0.001).\n\n3.3. Emotional Indicators\nResults indicate significant differences of emotional indicators between T-before (13–19 January, 2020) and T-after (20–26 January, 2020), as shown in Table 3. After 20 January, negative emotional indicators of psychological traits increased in anxiety (t (17,747) = −35.962, p \u003c 0.001), depression (t (17,747) = −10.717, p \u003c 0.001), and indignation (t (17,747) = 5.500, p \u003c 0.001), while positive emotional indicators of psychological traits decreased in Oxford happiness (t (17,747) = 3.120, p \u003c 0.01).\n\n3.4. Cognitive Indicators\nWe found significant differences in cognitive indicators between T-before (13–19 January, 2020) and T-after (20–26 January, 2020), as shown in Table 4. After 20 January, cognitive indicators of psychological traits increased in social risk judgement (t (17,747) = 3.120, p \u003c 0.01), but decreased in life satisfaction (t (17,747) = 5.500, p \u003c 0.001)."}