Acta Psychologica Sinica ›› 2021, Vol. 53 ›› Issue (2): 155-169.doi: 10.3724/SP.J.1041.2021.00155
• Reports of Empirical Studies • Previous Articles Next Articles
LUO Fang1, JIANG Liming1, TIAN Xuetao2, XIAO Mengge1, MA Yanzhen3, ZHANG Sheng3()
Received:
2020-04-22
Published:
2021-02-25
Online:
2020-12-29
Contact:
ZHANG Sheng
E-mail:zhangsheng@bnu.edu.cn
Supported by:
LUO Fang, JIANG Liming, TIAN Xuetao, XIAO Mengge, MA Yanzhen, ZHANG Sheng. (2021). Shyness prediction and language style model construction of elementary school students. Acta Psychologica Sinica, 53(2), 155-169.
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URL: https://journal.psych.ac.cn/acps/EN/10.3724/SP.J.1041.2021.00155
Sample size | Shyness behavior | Shyness cognition | Shyness emotion | |||
---|---|---|---|---|---|---|
1 | 0 | 1 | 0 | 1 | 0 | |
Number of training sets | 138 | 907 | 228 | 817 | 176 | 869 |
Number of test sets | 38 | 223 | 53 | 208 | 41 | 220 |
Table 1 Ratios of the training and test sets
Sample size | Shyness behavior | Shyness cognition | Shyness emotion | |||
---|---|---|---|---|---|---|
1 | 0 | 1 | 0 | 1 | 0 | |
Number of training sets | 138 | 907 | 228 | 817 | 176 | 869 |
Number of test sets | 38 | 223 | 53 | 208 | 41 | 220 |
Member of C group | Not a member of C group | |
---|---|---|
Classified as a member of C group | TP | FP |
Classified as not a member of C group | FN | TN |
Table 2 Classification results of the model and actual distribution of the data
Member of C group | Not a member of C group | |
---|---|---|
Classified as a member of C group | TP | FP |
Classified as not a member of C group | FN | TN |
Variable | Teachers’ ratings-behavior | Teachers’ ratings-cognition | Teachers’ ratings-emotion | Teachers’ ratings-shyness |
---|---|---|---|---|
Students’ self-ratings-behavior | 0.205 | 0.514 | 0.419 | 0.415 |
Students’ self-ratings-cognition | -0.170 | 0.213 | -0.092 | -0.008 |
Students’ self-ratings-emotion | 0.067 | 0.332 | 0.084 | 0.181 |
Students’ self-ratings-shyness | 0.058 | 0.421 | 0.161 | 0.239 |
Table 3 The correlation between teachers’ ratings and students’ self-ratings
Variable | Teachers’ ratings-behavior | Teachers’ ratings-cognition | Teachers’ ratings-emotion | Teachers’ ratings-shyness |
---|---|---|---|---|
Students’ self-ratings-behavior | 0.205 | 0.514 | 0.419 | 0.415 |
Students’ self-ratings-cognition | -0.170 | 0.213 | -0.092 | -0.008 |
Students’ self-ratings-emotion | 0.067 | 0.332 | 0.084 | 0.181 |
Students’ self-ratings-shyness | 0.058 | 0.421 | 0.161 | 0.239 |
Dimensions | Sample size | Sample proportion | Minimum number of words | Maximum number of words | Mean of total number of words | Standard deviation of total number of words |
---|---|---|---|---|---|---|
Behavior | ||||||
1 | 281 | 21.52% | 62 | 353086 | 7338.62 | 21711.80 |
0 | 1025 | 78.48% | 78 | 292321 | 10114.79 | 31150.93 |
Cognition | ||||||
1 | 176 | 13.48% | 137 | 152657 | 6056.41 | 12702.45 |
0 | 1130 | 86.52% | 62 | 353086 | 8227.89 | 25375.75 |
Emotion | ||||||
1 | 217 | 16.62% | 95 | 199348 | 7957.13 | 21606.92 |
0 | 1089 | 83.38% | 62 | 353086 | 7931.17 | 24538.95 |
Table 4 Results of the descriptive statistic of the groups
Dimensions | Sample size | Sample proportion | Minimum number of words | Maximum number of words | Mean of total number of words | Standard deviation of total number of words |
---|---|---|---|---|---|---|
Behavior | ||||||
1 | 281 | 21.52% | 62 | 353086 | 7338.62 | 21711.80 |
0 | 1025 | 78.48% | 78 | 292321 | 10114.79 | 31150.93 |
Cognition | ||||||
1 | 176 | 13.48% | 137 | 152657 | 6056.41 | 12702.45 |
0 | 1130 | 86.52% | 62 | 353086 | 8227.89 | 25375.75 |
Emotion | ||||||
1 | 217 | 16.62% | 95 | 199348 | 7957.13 | 21606.92 |
0 | 1089 | 83.38% | 62 | 353086 | 7931.17 | 24538.95 |
Shyness behavior | Shyness cognition | Shyness emotion | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
Category | Direction | χ2 | Category | Direction | χ2 | Category | Direction | χ2 | |||
C111 | Average number of words per sentence | - | 534.36 | C111 | Average number of words per sentence | - | 534.36 | C111 | Average number of words per sentence | - | 534.36 |
C33 | Social words | - | 159.70 | C33 | Social words | - | 579.58 | C33 | Social words | - | 293.28 |
C34 | Family | - | 377.82 | C34 | Family | - | 274.53 | C34 | Family | - | 236.62 |
C28 | Colloquialism | + | 146.82 | C28 | Colloquialism | - | 300.67 | C28 | Colloquialism | - | 131.76 |
C32 | Filler | + | 143.77 | C32 | Filler | - | 331.44 | C32 | Filler | - | 100.69 |
C67 | Cognition words | + | 421.76 | C67 | Cognition words | - | 301.68 | C67 | Cognition words | - | 270.85 |
C5 | First Person Plural Pronoun | + | 152.95 | C5 | First Person Plural Pronoun | - | 406.14 | C3 | Personal Pronoun | - | 132.93 |
C6 | Second Person Pronoun | - | 276.34 | C2 | Pronoun | - | 256.97 | C74 | Inclusive words | - | 225.94 |
C31 | Pause filler | + | 163.20 | C3 | Personal Pronoun | - | 334.49 | C69 | Causal words | + | 112.08 |
C72 | Certain words | + | 204.60 | C74 | Inclusive words | - | 121.67 | C1 | Functional words | - | 270.38 |
C75 | Exclusive words | + | 144.94 | C75 | Exclusive words | - | 243.69 | C22 | Interjunction | - | 116.55 |
C69 | Causal words | + | 228.00 | C15 | Conjunctions | - | 126.65 | C11 | Verbs | - | 334.79 |
C1 | Functional words | + | 359.20 | C90 | Achievement words | + | 118.25 | C91 | Leisure words | - | 271.43 |
C13 | Adverbs | + | 315.86 | C85 | Relative words | + | 104.50 | C23 | Tense Marker | - | 319.35 |
C15 | Conjunctions | + | 574.02 | C87 | Space words | + | 226.83 | C27 | Prolong words | - | 334.47 |
C91 | Leisure | - | 307.10 | C94 | Religion words | - | 332.24 | C85 | Relative words | - | 424.11 |
C98 | Animal | - | 477.33 | C88 | Time words | - | 174.19 | ||||
C24 | Past marker | + | 113.93 | C86 | Motion words | - | 367.58 | ||||
C89 | Work | + | 270.43 | C80 | Biological words | - | 111.72 | ||||
C76 | Perception words | - | 340.46 | C84 | Digestion words | - | 126.11 | ||||
C77 | Look | - | 309.74 | ||||||||
C78 | Hear | - | 204.74 | ||||||||
C94 | Religion words | + | 139.86 |
Table 5 Feature extraction for each dimension
Shyness behavior | Shyness cognition | Shyness emotion | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
Category | Direction | χ2 | Category | Direction | χ2 | Category | Direction | χ2 | |||
C111 | Average number of words per sentence | - | 534.36 | C111 | Average number of words per sentence | - | 534.36 | C111 | Average number of words per sentence | - | 534.36 |
C33 | Social words | - | 159.70 | C33 | Social words | - | 579.58 | C33 | Social words | - | 293.28 |
C34 | Family | - | 377.82 | C34 | Family | - | 274.53 | C34 | Family | - | 236.62 |
C28 | Colloquialism | + | 146.82 | C28 | Colloquialism | - | 300.67 | C28 | Colloquialism | - | 131.76 |
C32 | Filler | + | 143.77 | C32 | Filler | - | 331.44 | C32 | Filler | - | 100.69 |
C67 | Cognition words | + | 421.76 | C67 | Cognition words | - | 301.68 | C67 | Cognition words | - | 270.85 |
C5 | First Person Plural Pronoun | + | 152.95 | C5 | First Person Plural Pronoun | - | 406.14 | C3 | Personal Pronoun | - | 132.93 |
C6 | Second Person Pronoun | - | 276.34 | C2 | Pronoun | - | 256.97 | C74 | Inclusive words | - | 225.94 |
C31 | Pause filler | + | 163.20 | C3 | Personal Pronoun | - | 334.49 | C69 | Causal words | + | 112.08 |
C72 | Certain words | + | 204.60 | C74 | Inclusive words | - | 121.67 | C1 | Functional words | - | 270.38 |
C75 | Exclusive words | + | 144.94 | C75 | Exclusive words | - | 243.69 | C22 | Interjunction | - | 116.55 |
C69 | Causal words | + | 228.00 | C15 | Conjunctions | - | 126.65 | C11 | Verbs | - | 334.79 |
C1 | Functional words | + | 359.20 | C90 | Achievement words | + | 118.25 | C91 | Leisure words | - | 271.43 |
C13 | Adverbs | + | 315.86 | C85 | Relative words | + | 104.50 | C23 | Tense Marker | - | 319.35 |
C15 | Conjunctions | + | 574.02 | C87 | Space words | + | 226.83 | C27 | Prolong words | - | 334.47 |
C91 | Leisure | - | 307.10 | C94 | Religion words | - | 332.24 | C85 | Relative words | - | 424.11 |
C98 | Animal | - | 477.33 | C88 | Time words | - | 174.19 | ||||
C24 | Past marker | + | 113.93 | C86 | Motion words | - | 367.58 | ||||
C89 | Work | + | 270.43 | C80 | Biological words | - | 111.72 | ||||
C76 | Perception words | - | 340.46 | C84 | Digestion words | - | 126.11 | ||||
C77 | Look | - | 309.74 | ||||||||
C78 | Hear | - | 204.74 | ||||||||
C94 | Religion words | + | 139.86 |
Dimensions | Decision tree | Random forest | Logistic regression | K-nearest neighbor | Multilayer perceptron | Support vector machine | ||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Behavior | Cognition | Emotion | Behavior | Cognition | Emotion | Behavior | Cognition | Emotion | Behavior | Cognition | Emotion | Behavior | Cognition | Emotion | Behavior | Cognition | Emotion | |
Precision- ordinary | 0.86 | 0.78 | 0.85 | 0.88 | 0.84 | 0.87 | 0.86 | 0.80 | 0.84 | 0.85 | 0.79 | 0.84 | 0.83 | 0.81 | 0.85 | 0.84 | 0.82 | 0.87 |
Precision- shy | 0.16 | 0.16 | 0.18 | 0.29 | 0.25 | 0.20 | 0.50 | 0.27 | 0.15 | 0.00 | 0.14 | 0.20 | 0.10 | 0.27 | 0.16 | 0.11 | 0.28 | 0.23 |
Recall- ordinary | 0.86 | 0.75 | 0.82 | 0.86 | 0.93 | 0.68 | 0.99 | 0.92 | 0.90 | 0.99 | 0.94 | 0.98 | 0.63 | 0.89 | 0.67 | 0.75 | 0.78 | 0.74 |
Recall-shy | 0.16 | 0.19 | 0.22 | 0.29 | 0.15 | 0.44 | 0.05 | 0.11 | 0.10 | 0.00 | 0.04 | 0.02 | 0.24 | 0.17 | 0.34 | 0.18 | 0.34 | 0.42 |
F1-ordinary | 0.86 | 0.77 | 0.83 | 0.89 | 0.67 | 0.76 | 0.92 | 0.86 | 0.87 | 0.00 | 0.86 | 0.91 | 0.71 | 0.85 | 0.75 | 0.79 | 0.80 | 0.80 |
F1-shy | 0.16 | 0.17 | 0.20 | 0.28 | 0.34 | 0.28 | 0.10 | 0.16 | 0.12 | 0.00 | 0.06 | 0.04 | 0.14 | 0.21 | 0.22 | 0.14 | 0.31 | 0.29 |
Macro F1 | 0.51 | 0.47 | 0.52 | 0.57 | 0.56 | 0.55 | 0.59 | 0.53 | 0.50 | 0.46 | 0.48 | 0.51 | 0.45 | 0.53 | 0.51 | 0.47 | 0.56 | 0.56 |
Table 6 Results of the model predictions
Dimensions | Decision tree | Random forest | Logistic regression | K-nearest neighbor | Multilayer perceptron | Support vector machine | ||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Behavior | Cognition | Emotion | Behavior | Cognition | Emotion | Behavior | Cognition | Emotion | Behavior | Cognition | Emotion | Behavior | Cognition | Emotion | Behavior | Cognition | Emotion | |
Precision- ordinary | 0.86 | 0.78 | 0.85 | 0.88 | 0.84 | 0.87 | 0.86 | 0.80 | 0.84 | 0.85 | 0.79 | 0.84 | 0.83 | 0.81 | 0.85 | 0.84 | 0.82 | 0.87 |
Precision- shy | 0.16 | 0.16 | 0.18 | 0.29 | 0.25 | 0.20 | 0.50 | 0.27 | 0.15 | 0.00 | 0.14 | 0.20 | 0.10 | 0.27 | 0.16 | 0.11 | 0.28 | 0.23 |
Recall- ordinary | 0.86 | 0.75 | 0.82 | 0.86 | 0.93 | 0.68 | 0.99 | 0.92 | 0.90 | 0.99 | 0.94 | 0.98 | 0.63 | 0.89 | 0.67 | 0.75 | 0.78 | 0.74 |
Recall-shy | 0.16 | 0.19 | 0.22 | 0.29 | 0.15 | 0.44 | 0.05 | 0.11 | 0.10 | 0.00 | 0.04 | 0.02 | 0.24 | 0.17 | 0.34 | 0.18 | 0.34 | 0.42 |
F1-ordinary | 0.86 | 0.77 | 0.83 | 0.89 | 0.67 | 0.76 | 0.92 | 0.86 | 0.87 | 0.00 | 0.86 | 0.91 | 0.71 | 0.85 | 0.75 | 0.79 | 0.80 | 0.80 |
F1-shy | 0.16 | 0.17 | 0.20 | 0.28 | 0.34 | 0.28 | 0.10 | 0.16 | 0.12 | 0.00 | 0.06 | 0.04 | 0.14 | 0.21 | 0.22 | 0.14 | 0.31 | 0.29 |
Macro F1 | 0.51 | 0.47 | 0.52 | 0.57 | 0.56 | 0.55 | 0.59 | 0.53 | 0.50 | 0.46 | 0.48 | 0.51 | 0.45 | 0.53 | 0.51 | 0.47 | 0.56 | 0.56 |
Dimensions | 1 | 2 | 3 | 4 | 5 | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Behavior | Cognition | Emotion | Behavior | Cognition | Emotion | Behavior | Cognition | Emotion | Behavior | Cognition | Emotion | Behavior | Cognition | Emotion | |
Precision- ordinary | 0.88 | 0.81 | 0.87 | 0.85 | 0.75 | 0.86 | 0.89 | 0.78 | 0.86 | 0.88 | 0.83 | 0.86 | 0.89 | 0.79 | 0.85 |
Precision-shy | 0.26 | 0.35 | 0.20 | 0.20 | 0.43 | 0.26 | 0.18 | 0.27 | 0.20 | 0.19 | 0.33 | 0.19 | 0.22 | 0.29 | 0.18 |
Recall-ordinary | 0.86 | 0.93 | 0.68 | 0.87 | 0.96 | 0.76 | 0.7 | 0.87 | 0.77 | 0.73 | 0.85 | 0.69 | 0.74 | 0.82 | 0.62 |
Recall-shy | 0.29 | 0.15 | 0.44 | 0.17 | 0.09 | 0.4 | 0.43 | 0.17 | 0.33 | 0.39 | 0.29 | 0.39 | 0.44 | 0.25 | 0.44 |
F1-ordinary | 0.87 | 0.87 | 0.76 | 0.86 | 0.84 | 0.81 | 0.78 | 0.82 | 0.81 | 0.80 | 0.84 | 0.77 | 0.81 | 0.80 | 0.72 |
F1-shy | 0.27 | 0.21 | 0.28 | 0.18 | 0.15 | 0.32 | 0.25 | 0.21 | 0.25 | 0.26 | 0.31 | 0.26 | 0.29 | 0.27 | 0.26 |
Macro F1 | 0.57 | 0.56 | 0.55 | 0.52 | 0.56 | 0.57 | 0.55 | 0.52 | 0.54 | 0.55 | 0.57 | 0.53 | 0.57 | 0.54 | 0.52 |
Table 7 Cross-validation results for the random forest model
Dimensions | 1 | 2 | 3 | 4 | 5 | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Behavior | Cognition | Emotion | Behavior | Cognition | Emotion | Behavior | Cognition | Emotion | Behavior | Cognition | Emotion | Behavior | Cognition | Emotion | |
Precision- ordinary | 0.88 | 0.81 | 0.87 | 0.85 | 0.75 | 0.86 | 0.89 | 0.78 | 0.86 | 0.88 | 0.83 | 0.86 | 0.89 | 0.79 | 0.85 |
Precision-shy | 0.26 | 0.35 | 0.20 | 0.20 | 0.43 | 0.26 | 0.18 | 0.27 | 0.20 | 0.19 | 0.33 | 0.19 | 0.22 | 0.29 | 0.18 |
Recall-ordinary | 0.86 | 0.93 | 0.68 | 0.87 | 0.96 | 0.76 | 0.7 | 0.87 | 0.77 | 0.73 | 0.85 | 0.69 | 0.74 | 0.82 | 0.62 |
Recall-shy | 0.29 | 0.15 | 0.44 | 0.17 | 0.09 | 0.4 | 0.43 | 0.17 | 0.33 | 0.39 | 0.29 | 0.39 | 0.44 | 0.25 | 0.44 |
F1-ordinary | 0.87 | 0.87 | 0.76 | 0.86 | 0.84 | 0.81 | 0.78 | 0.82 | 0.81 | 0.80 | 0.84 | 0.77 | 0.81 | 0.80 | 0.72 |
F1-shy | 0.27 | 0.21 | 0.28 | 0.18 | 0.15 | 0.32 | 0.25 | 0.21 | 0.25 | 0.26 | 0.31 | 0.26 | 0.29 | 0.27 | 0.26 |
Macro F1 | 0.57 | 0.56 | 0.55 | 0.52 | 0.56 | 0.57 | 0.55 | 0.52 | 0.54 | 0.55 | 0.57 | 0.53 | 0.57 | 0.54 | 0.52 |
[1] | Agarwal, A., Xie, B., Vovsha, I., Rambow, O., & Passonneau, R. J. (2011 June). Sentiment analysis of twitter data. In Proceedings of the Workshop on Languages in Social Media (pp. 30-38). |
[2] | Allport, G. W. (1937). Personality: A psychological interpretation. American Journal of Sociology, 45 (1), 48-50. |
[3] | Argamon, S., Dhawle, S., Koppel, M., & Pennebaker, J. W. (2005 June). Lexical predictors of personality type. In Proceedings of the 2005 Joint Annual Meeting of the Interface and the Classification Society of North America (pp. 1-16). |
[4] |
Arroyo, A., Nevárez, N., Segrin, C., & Harwood, J. (2012). The association between parent and adult child shyness, social skills, and perceived family communication. Journal of Family Communication, 12 (4), 249-264.
doi: 10.1080/15267431.2012.686941 URL |
[5] | Aung, Z. M. M., & Myint, P. H. (2019 July). Personality prediction based on content of Facebook users: A literature review. In 2019 20th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (pp. 34-38). |
[6] |
Azucar, D., Marengo, D., & Settanni, M. (2018). Predicting the big 5 personality traits from digital footprints on social media: a meta-analysis. Personality and Individual Differences, 124, 150-159.
doi: 10.1016/j.paid.2017.12.018 URL |
[7] |
Baardstu, S., Coplan, R. J., Karevold, E. B., Laceulle, O. M., & von Soest, T. (2019). Longitudinal pathways from shyness in early childhood to personality in adolescence: do peers matter? Journal of Research on Adolescence, 30 (2), 362-379.
doi: 10.1111/jora.v30.s2 URL |
[8] | Bachrach, Y., Graepel, T., Kohli, P., Kosinski, M., & Stillwell, D. (2014 May). Your digital image: factors behind demographic and psychometric predictions from social network profiles. In Proceedings of the 2014 International Conference on Autonomous Agents and Multi-agent Systems (pp. 1649-1650). |
[9] | Bai, S. T., Hao, B. B., Li, A., Nie, D., & Zhu, T. S. (2014). Depression and anxiety prediction on microblogs. Journal of University of Chinese Academy of Sciences, 31 (6), 814-820. |
[10] |
Brodt, S. E., & Zimbardo, P. G. (1981). Modifying shyness-related social behavior through symptom misattribution. Journal of Personality and Social Psychology, 41 (3), 437-449.
doi: 10.1037//0022-3514.41.3.437 URL pmid: 7288563 |
[11] | Bruch, M. A. (1989). Familial and developmental antecedents of social phobia: issues and findings. Clinical Psychology Review, 9 (1), 37-47. |
[12] | Caspi, A., Elder, G. H., & Bem, D. J. (1988). Moving away from the world: Life-course patterns of shy children. Developmental Psychology, 24 (6), 824-831. |
[13] |
Cassin, S. E., & von, Ranson K. M. (2005). Personality and eating disorders: A decade in review. Clinical Psychology Review, 25 (7), 895-916.
doi: 10.1016/j.cpr.2005.04.012 URL pmid: 16099563 |
[14] | Cattell, R. B. (1943). The description of personality. Psychological Review, 50, 559-594. |
[15] | Chamansingh, N., & Hosein, P. (2016 September). Efficient sentiment classification of Twitter feeds. In 2016 IEEE International Conference on Knowledge Engineering and Applications (pp. 78-82). |
[16] | Cheek, J. M., & Buss, A. H. (1981). Shyness and sociability. Journal of Personality and Social Psychology, 41 (2), 330-339. |
[17] |
Chen, L. S., Gong, T., Kosinski, M., Stillwell, D., & Davidson, R. L. (2017). Building a profile of subjective well-being for social media users. Plos One, 12 (11), e0187278.
URL pmid: 29135991 |
[18] | Chen, X. Y. (2010). Shyness-inhibition in childhood and adolescence: A cross-cultural perspective. In K. H. Rubin & R. J. Coplan (Eds.), The development of shyness and social withdrawal (pp. 213-235). New York: Guilford Press. |
[19] |
Cheng, Q., Li, T. M., Kwok, C. L., Zhu, T., & Yip, P. S. (2017). Assessing suicide risk and emotional distress in Chinese social media: A text mining and machine learning study. Journal of Medical Internet Research, 19 (7), e243.
doi: 10.2196/jmir.7276 URL pmid: 28694239 |
[20] |
Coplan, R. J., Prakash, K., O'Neil, K., & Armer, M. (2004). Do you "want" to play? distinguishing between conflicted shyness and social disinterest in early childhood. Developmental Psychology, 40 (2), 244-258.
doi: 10.1037/0012-1649.40.2.244 URL pmid: 14979764 |
[21] |
Dennissen, J. J. A., Asendorpf, J. B., & van, Aken, M. A. G. (2008). Childhood personality predicts long‐term trajectories of shyness and aggressiveness in the context of demographic transitions in emerging adulthood. Journal of Personality, 76 (1), 67-100.
doi: 10.1111/j.1467-6494.2007.00480.x URL pmid: 18186711 |
[22] | Diamantidis, N. A., Karlis, D., & Giakoumakis, E. A. (2000). Unsupervised stratification of cross-validation for accuracy estimation. Artificial Intelligence, 116 (1-2), 1-16. |
[23] | Dörre, J., Gerstl, P., & Seiffert, R. (1999 August). Text mining: finding nuggets in mountains of textual data. In Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 398-401). |
[24] |
Eisenberg, N., Shepard, S. A., Fabes, R. A., Murphy, B. C., & Guthrie, I. K. (1998). Shyness and children’s emotionality, regulation, and coping: Contemporaneous, longitudinal, and across-context relations. Child Development, 69 (3), 767-790.
URL pmid: 9680684 |
[25] | Engfer, A. (1993). Antecedents and consequences of shyness in boys and girls: A 6-year longitudinal study. In K. H. Rubin, & J. Asendorpf (Eds.), Social withdrawal, inhibition, and shyness in childhood (pp. 49-79). London: Psychology Press. |
[26] | Evans, M. (1993). Language, performance, academic performance, and signs of shyness. In K. H. Rubin & R. J. Coplan (Eds.), The development of shyness and social withdrawal (pp. 172-212). New York: Guilford Press. |
[27] | Eysenck, H. J., & Cookson, D. (1969). Personality in primary school children: Ability and achievement. British Journal of Educational Psychology, 39 (2), 109-122. |
[28] | Farnadi, G., Zoghbi, S., Moens, M. F., & de Cock, M. (2013 July). Recognising personality traits using Facebook status updates. In Seventh International AAAI Conference on Weblogs and Social Media (pp.14-18). |
[29] |
Fast, L. A., & Funder, D. C. (2008). Personality as manifest in word use: correlations with self-report, acquaintance report, and behavior. Journal of Personality and Social Psychology, 94 (2), 334-346.
URL pmid: 18211181 |
[30] | Feldman, R., & Sanger, J. (1993). The text mining handbook: Advanced approaches in analyzing unstructured data. Cambridge University Press. |
[31] | Findlay, L. C., Coplan, R. J., & Bowker, A. (2009). Keeping it all inside: shyness, internalizing coping strategies and socio-emotional adjustment in middle childhood. International Journal of Behavioral Development, 33 (1), 47-54. |
[32] | Forman, G. (2003). An extensive empirical study of feature selection metrics for text classification. Journal of Machine Learning Research, 3, 1289-1305. |
[33] | Friedman, J., Hastie, T., & Tibshirani, R. (2001). The elements of statistical learning. New York: Springer series in statistics. |
[34] |
Geisser, S. (1975). The predictive sample reuse method with applications. Journal of the American Statistical Association, 70 (350), 320-328.
doi: 10.1080/01621459.1975.10479865 URL |
[35] | Gill, A. J., Nowson, S., & Oberlander, J. (2009 March). What are they blogging about? Personality, topic and motivation in blogs. In Third International AAAI Conference on Weblogs and Social Media. |
[36] | Goldberg, L. R. (1982). From Ace to Zombie: some explorations in the language of personality. Advances in Personality Assessment, 1, 203-234. |
[37] | Gu, H. Q., Wang, J., Wang, Z. W., Zhuang, B. J., & Su, F. (2018 July). Modeling of user portrait through social media. In 2018 IEEE International Conference on Multimedia and Expo (pp. 1-6). |
[38] | Guo, L., Vargo, C. J., Pan, Z. X., Ding, W. C., & Ishwar, P. (2016). Big social data analytics in journalism and mass communication: comparing dictionary-based text analysis and unsupervised topic modeling. Journalism and Mass Communication Quarterly, 93 (2), 332-359. |
[39] | Han, L., Gao, F. Q., Guo, Y. Y., & Wang, P. (2011). The relationships between personality and shyness: Mediation and moderation effects. Journal of Psychological Science, 34 (4), 889-893. |
[40] | Hawkins, D. M., Basak, S. C., & Mills, D. (2003). Assessing model fit by cross-validation. Journal of Chemical Information and Modeling, 43 (2), 579-586. |
[41] | He, H. B., & Garcia, E. A. (2009). Learning from imbalanced data. IEEE Transactions on Knowledge and Data Engineering, 21 (9), 1263-1284. |
[42] | Henderson, L., Gilbert, P., & Zimbardo, P. (2014) Shyness, social anxiety, and social phobia. In S. G. Hofmann & P. M. DiBartolo (Eds.), Social anxiety (pp. 95-115). London: Academic Press. |
[43] | Hirsh, J. B., & Peterson, J. B. (2009). Personality and language use in self-narratives. Journal of Research in Personality, 43 (3), 524-527. |
[44] | Ho, D. Y. F. (1986) Chinese patterns of socialization: a critical review. In M. H. Bond (Ed.), The psychology of the Chinese people (pp. 1-37). New York: Oxford University Press. |
[45] |
Hofstee, W. K., de Raad, B., & Goldberg, L. R. (1992). Integration of the big five and circumplex approaches to trait structure. Journal of Personality and Social Psychology, 63 (1), 146-163.
doi: 10.1037//0022-3514.63.1.146 URL pmid: 1494982 |
[46] | Huang, L. N. (1999). Family communication patterns and personality characteristics. Communication Quarterly, 47 (2), 230-243. |
[47] | Huang, X. T., & Zheng, Y. (2000). Self-integration on time perspective: I. projective test for the psychological structure. Acta Psychologica Sinica, 32 (1), 30-35. |
[48] | Jones, K. M., Schulkin, J., & Schmidt, L. A. (2014). Shyness: subtypes, psychosocial correlates, and treatment interventions. Psychology, 5 (3), 244-254. |
[49] |
Kagan, J. (1997). Temperament and the reactions to unfamiliarity. Child Development, 68 (1), 139-143.
URL pmid: 9084130 |
[50] |
Karevold, E., Ystrom, E., Coplan, R. J., Sanson, A. V., & Mathiesen, K. S. (2012). A prospective longitudinal study of shyness from infancy to adolescence: Stability, age-related changes, and prediction of socio-emotional functioning. Journal of Abnormal Child Psychology, 40 (7), 1167-1177.
doi: 10.1007/s10802-012-9635-6 URL pmid: 22527608 |
[51] |
Kwiatkowska, M. M., Jułkowski, T., Rogoza, R., Żemojtel- Piotrowska, M., & Fatfouta, R. (2019). Narcissism and trust: differential impact of agentic, antagonistic, and communal narcissism. Personality and Individual Differences, 137, 139-143.
doi: 10.1016/j.paid.2018.08.027 URL |
[52] |
La Sala, L., Skues, J., & Grant, S. (2014). Personality traits and Facebook use: the combined/interactive effect of extraversion, neuroticism and conscientiousness. Social Networking, 3 (5), 211-219.
doi: 10.4236/sn.2014.35026 URL |
[53] |
Laserna, C. M., Seih, Y. T., & Pennebaker, J. W. (2014). Um… who like says you know: filler word use as a function of age, gender, and personality. Journal of Language and Social Psychology, 33 (3), 328-338.
doi: 10.1177/0261927X14526993 URL |
[54] |
Lawrence, B., & Bennett, S. (1992). Shyness and education: the relationship between shyness, social class and personality variables in adolescents. British Journal of Educational Psychology, 62 (2), 257-263.
doi: 10.1111/bjep.1992.62.issue-2 URL |
[55] | Leary, M. R. (1983). Understanding social anxiety: Social, personality, and clinical perspectives. Beverly Hills: Sage Publication. |
[56] | Leary, M. R. (1986). Affective and behavioral components of shyness. In W. H. Jones, J. M. Cheek, & S. R. Briggs (Eds.), Shyness (pp. 27-38). Springer Science & Business Media. |
[57] | Leary, M. R., & Schlenker, B. R. (1981). The social psychology of shyness: A self-presentation model. In J. T. Tedeschi (Ed.), Impression management theory and social psychological research (pp. 335-358). London: Academic Press. |
[58] | Lewinsky, H. (1941). The nature of shyness. British Journal of Psychology, 32 (2), 105-113. |
[59] | Li, Y. H., Hu, W. D., Xu, Z. P., & Han, W. Q. (2005). Study and progress of socially desirable responding problem in personality measurement. Chinese Journal of Clinical Rehabilitation, 9 (8), 119-121. |
[60] | Lin, B. Y., Xu, F. F., Zhu, K., & Hwang, S. W. (2018, July). Mining cross-cultural differences and similarities in social media. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (pp. 709-719). |
[61] | Liu, X. Y., & Zhou, Z. H. (2006, December). The influence of class imbalance on cost-sensitive learning: An empirical study. In Sixth International Conference on Data Mining (pp. 970-974). |
[62] |
López, V., Fernández, A., García, S., Palade, V., & Herrera, F. (2013). An insight into classification with imbalanced data: Empirical results and current trends on using data intrinsic characteristics. Information Sciences, 250, 113-141.
doi: 10.1016/j.ins.2013.07.007 URL |
[63] | Luo, F., & Zhang, H. C. (2007). Methods of coping with faking of personality tests. Psychological Exploration, 27 (4), 78-82. |
[64] |
Mairesse, F., Walker, M. A., Mehl, M. R., & Moore, R. K. (2007). Using linguistic cues for the automatic recognition of personality in conversation and text. Journal of Artificial Intelligence Research, 30 (1), 457-500.
doi: 10.1613/jair.2349 URL |
[65] | Majumder, N., Poria, S., Gelbukh, A., & Cambria, E. (2017). Deep learning-based document modeling for personality detection from text. IEEE Intelligent Systems, 32 (2), 74-79. |
[66] | Markovikj, D., Gievska, S., Kosinski, M., & Stillwell, D. (2013, June). Mining Facebook data for predictive personality modeling. In Seventh International AAAI Conference on Weblogs and Social Media (pp. 23-26). |
[67] | Marouf, A. A., Hasan, M. K., & Mahmud, H. (2019 February). Identifying neuroticism from user generated content of social media based on psycholinguistic cues. In 2019 International Conference on Electrical, Computer and Communication Engineering (pp. 1-5). |
[68] |
Martin, B. (1961). The assessment of anxiety by physiological behavioral measures. Psychological Bulletin, 58, 234-255.
doi: 10.1037/h0045492 URL pmid: 13767312 |
[69] | Mccarthy, K., Zabar, B., & Weiss, G. (2005, August) Does cost-sensitive learning beat sampling for classifying rare classes? In International Workshop on Utility-based Data Mining (pp. 69-77). |
[70] |
Mehl, M. R., Gosling, S. D., & Pennebaker, J. W. (2006). Personality in its natural habitat: manifestations and implicit folk theories of personality in daily life. Journal of Personality and Social Psychology, 90 (5), 862-877.
doi: 10.1037/0022-3514.90.5.862 URL pmid: 16737378 |
[71] |
Narduzzi, K. J., & Jackson, T. (2000). Personality differences between eating‐disordered women and a nonclinical comparison sample: A discriminant classification analysis. Journal of Clinical Psychology, 56 (6), 699-710.
doi: 10.1002/(sici)1097-4679(200006)56:6<699::aid-jclp1>3.0.co;2-k URL pmid: 10877460 |
[72] | Norman, W. T. (1963). Toward an adequate taxonomy of personality attributes: Replicated factor structure in peer nomination personality ratings. Journal of Abnormal and Social Psychology, 66 (6), 574-583. |
[73] | Nowson, S. (2006). The language of weblogs: a study of genre and individual differences(Unpublished doctoral dissertation). University of Edinburgh. |
[74] | Oakes, M., Gaaizauskas, R., Fowkes, H., Jonsson, A., Wan, V., & Beaulieu, M. (2001, September). A method based on the chi-square test for document classification. In Proceedings of the 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (pp. 440-441). |
[75] | Oberlander, J., & Gill, A. J. (2006). Language with character: A stratified corpus comparison of individual differences in e-mail communication. Discourse Processes, 42 (3), 239-270. |
[76] | Oommen, T., Baise, L. G., & Vogel, R. M. (2011). Sampling bias and class imbalance in Maximum-likelihood Logistic Regression. Mathematical Geosciences, 43 (1), 99-120. |
[77] | Papamitsiou, Z., & Economides, A. A. (2017). Exhibiting achievement behavior during computer-based testing: What temporal trace data and personality traits tell us? Computers in Human Behavior, 75, 423-438. |
[78] | Paudel, S., Prasad, P. W. C., Alsadoon, A., Islam, M. R., & Elchouemi, A. (2018, July). Feature selection approach for twitter sentiment analysis and text classification based on Chi-Square and Naïve Bayes. In International Conference on Applications and Techniques in Cyber Security and Intelligence (pp. 281-298). |
[79] |
Pennebaker, J. W., & King, L. A. (1999). Linguistic styles: language use as an individual difference. Journal of Personality and Social Psychology, 77 (6), 1296-1312.
doi: 10.1037//0022-3514.77.6.1296 URL pmid: 10626371 |
[80] | Pennebaker, J. W., Boyd, R. L., Jordan, K., & Blackburn, K. (2015). The development and psychometric properties of LIWC2015. Austin, TX: University of Texas at Austin. doi: 10.15781/T29G6Z |
[81] | Pilkonis, P. A. (1977). The behavioral consequences of shyness. Journal of Personality, 45 (4), 596-611. |
[82] | Qiu, L., Lin, H., Ramsay, J., & Yang, F. (2012). You are what you tweet: personality expression and perception on twitter. Journal of Research in Personality, 46 (6), 710-718. |
[83] | Qiu, L., Lu, J. H., Ramsay, J., Yang, S. S., Qu, W. N., & Zhu, T. Z. (2017). Personality expression in Chinese language use. International Journal of Psychology, 52 (6), 463-472. |
[84] | Rubin, K. H., Coplan, R. J., Fox, N. A., & Calkins, S. D. (1995). Emotionality, emotion regulation, and preschoolers' social adaptation. Development and Psychopathology, 7 (1), 49-62. |
[85] | Sandoval, J., & Echandia, A. (1994). Behavior assessment system for children. Journal of School Psychology, 32 (4), 419-425. |
[86] | Sato, E., Matsuda, K. H., & Carducci, B. J. (2018). A factor analytical investigation of the Japanese translation of the Cheek-Buss Shyness Scale in support of the three- component model of shyness. Personality and Individual Differences, 124, 160-167. |
[87] |
Schlenker, B. R., & Leary, M. R. (1982). Social anxiety and self-presentation: A conceptualization model. Psychological Bulletin, 92 (3), 641-669.
doi: 10.1037/0033-2909.92.3.641 URL pmid: 7156261 |
[88] | Shen, T. C., Jia, J., Shen, G. Y., Feng, F. L., He, X. N., Luan, H. B., … Hall, W. (2018, July). Cross-domain depression detection via harvesting social media. In Proceedings of the 27th International Joint Conference on Artificial Intelligence (pp. 1611-1617). |
[89] | Skowron, M., Tkalčič, M., Ferwerda, B., & Schedl, M. (2016, April). Fusing social media cues: Personality prediction from Twitter and Instagram. In Proceedings of the 25th International Conference Companion on World Wide Web (pp. 107-108). |
[90] | Sun, Y. Q., Fan, Y. M., Wang, P., Gong, R. Y., & Gao, F. Q. (2009). Relationship among shyness, posttraumatic stress disorder symptom and mental health of children who lost their relatives in WenChuan earthquake. Chinese Journal of Clinical Psychology, 17 (4), 484-486. |
[91] |
Tadesse, M. M., Lin, H. F., Xu, B., & Yang, L. (2018). Personality predictions based on user behavior on the Facebook social media platform. IEEE Access, 6, 61959-61969.
doi: 10.1109/ACCESS.2018.2876502 URL |
[92] | Tandera, T., Hendro , Suhartono, D., Wongso, R., & Prasetio, Y. L. (2017). Personality prediction system from Facebook users. Procedia Computer Science, 116, 604-611. |
[93] | Tausczik, Y. R., & Pennebaker, J. W. (2010). The psychological meaning of words: LIWC and computerized text analysis methods. Journal of Language and Social Psychology, 29 (1), 24-54. |
[94] | Ting, K. M. (2002). An instance-weighting method to induce cost-sensitive trees. IEEE Transactions on Knowledge and Data Engineering, 14 (3), 659-665. |
[95] | Wan, W. Y., Sun, J. M., Liu, J. H., Yang, S. W., Liu, M. M., Xue, J., … Liu, X. Q. (2019). Using social media to explore the linguistic features in female adults with childhood sexual abuse by Linguistic Inquiry and Word Count. Human Behavior and Emerging Technologies, 1 (3), 181-189. |
[96] | Wang, J. Y., Gan, S. Q., Zhao, N., Liu, T. L., Zhu, T. S. (2016). Chinese mood variation analysis based on Sina Weibo. Journal of University of Chinese Academy of Sciences, 33 (6), 815-824. |
[97] | Xu, C. R. (2001). The Study on the Relationships Among Elementary School Students' Self-esteem, Locus of Control, Parenting Style and Shyness (Unpublished master’s thesis). National Pingtung University. |
[98] | Xue, D., Wu, L. F., Hong, Z., Guo, S. Z., Gao, L., Wu, Z. Y., Zhong, X. F., & Sun, J. S. (2018). Deep learning-based personality recognition from text posts of online social networks. Applied Intelligence, 48 (11), 4232-4246. |
[99] |
Yarkoni, T. (2010). Personality in 100,000 words: A large-scale analysis of personality and word use among bloggers. Journal of Research in Personality, 44 (3), 363-373.
URL pmid: 20563301 |
[100] | Yuan, C. X., Wu, J. J., Li, H., & Wang, L. H. (2018, July). Personality recognition based on user generated content. In 2018 15th International Conference on Service Systems and Service Management (pp. 1-6). |
[101] | Zhang, C., Han, P. Y., Wang, X. Z., Huang, X. Y., Du, H., Wang, M. J., & Deng, X. (2012). Study on correlation between social anxiety and parental rearing style and shyness of children. Medical Journal of Chinese People's Health, 24 (19), 2401-2402. |
[102] | Zhao, N., Wang, Y. L., Li, S. J., Liu, X. Q., Wu, P. J., & Zhu, T. S. (2020). Psychological and behavioral impact of Wuhan lockdown and suggestions. Bulletin of Chinese Academy of Sciences, 35 (3), 264-272. |
[103] | Zhu, T. S. (2016). Psychological research and application in the era of big data. Beijing: Science Press. |
[104] | Zimbardo, P. G. (1977). Shyness: What it is what to do about it. Boston: Addison-Wesley Publishing Company. |
[105] | Zimbardo, P. G. (1982). Shyness and the stresses of the human connection. In L. Goldberger & S. Breznitz (Eds.), Handbook of stress: Theoretical and clinical aspects (pp. 466-481). New York: Free Press. |
[106] | Zimbardo, P. G., Pilkonis, P. A., & Norwood, R. M. (1975). The social disease called shyness. Psychology Today, 8 (12), 68-72. |
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