The role of information sentiment in popularity on social media: a psychoinformatic and electroencephalogram study

References

• Annett, M. (1970). A classification of hand preference by association analysis. British Journal of Psychology, 61(3), 303–321.
   PubMed Web of Science ®Google Scholar
• Aquado, L., Diequez-Risco, T., Mendez-Bertolo, C., Pozo, M. A., & Hinojosa, J. A. (2013). Priming effects on the N400 in the affective priming paradigm with facial expressions of emotion. Cognitive, Affective & Behavioral Neuroscience, 13(2), 284–296.
   PubMed Web of Science ®Google Scholar
• Bebbington, K., MacLeod, C., Ellison, T. M., & Fay, N. (2017). The sky is falling: Evidence of a negativity bias in the social transmission of information. Evolution and Human Behavior, 38, 92–101.
   Web of Science ®Google Scholar
• Berger, J. (2011). Arousal increases social transmission of information. Psychological Science, 22(7), 891–893.
   PubMed Web of Science ®Google Scholar
• Berger, J. (2014). Word of mouth and interpersonal communication: A review and directions for future research. Journal of Consumer Psychology, 24, 586–607.
   Web of Science ®Google Scholar
• Berger, J., & Milkman, K. L. (2012). What makes online content viral. Journal of Marketing Research, 49(2), 192–205.
   Web of Science ®Google Scholar
• Bollen, J., Pepe, A., & Mao, H. (2011). Modeling public mood and emotion: Twitter sentiment and socio-economic phenomena. In L. Adamic, R. Baeza-Yates, & S. Counts (Eds.), Proceedings of the fifth international AAAI conference on weblogs and social media. Palo Alto, CA
   Google Scholar
• Bradley, M. M., & Lang, P. J. (2000). Affective reactions to acoustic stimuli. Psychophysiology, 37(2), 204-215.
   Web of Science ®Google Scholar
• Case, R. (1992). The role of the frontal lobes in the regulation of cognitive development. Brain and Cognition, 20(1), 51–73.
   PubMed Web of Science ®Google Scholar
• Choi, M., & Toma, C. L. (2014). Social sharing through interpersonal media: Patterns and effects on emotional well-being. Computers in Human Behavior, 36, 530–541.
   Web of Science ®Google Scholar
• Corbetta, M., & Shulman, G. L. (2002). Control of goal-directed and stimulus-driven attention in the brain. Nature Reviews Neuroscience, 3, 201–215.
   PubMed Web of Science ®Google Scholar
• Dai, W., Han, D., Dai, Y., & Xu, D. (2015). Emotion recognition and affective computing on vocal social media. Information & Management, 52, 777–788.
   Web of Science ®Google Scholar
• Delaney-Busch, N., Wilkie, G., & Kuperberg, G. (2016). Vivid: How valence and arousal influence word processing under different task demands. Cognitive, Affective, & Behavioral Neuroscience, 16, 415–432.
   PubMed Web of Science ®Google Scholar
• Gabor, S., & Huberman Bernardo, A. (2010). Predicting the popularity of online content. Communications of the ACM, 53(8), 80–88.
   Web of Science ®Google Scholar
• Hajcak, G., & Nieuwenhuis, S. (2006). Reappraisal modulates the electrocortical response to unpleasant pictures. Cognitive, Affective, & Behavioral Neuroscience, 6, 291–297.
   PubMed Web of Science ®Google Scholar
• Hoedemaker, R. S., & Gordon, P. C. (2017). The onset and time course of semantic priming during rapid recognition of visual words. Journal of Experimental Psychology: Human Perception and Performance, 43(5), 881–902.
   PubMed Web of Science ®Google Scholar
• Hu, Y., Hu, C., Fu, S., Fang, M., & Xu, W. (2017). Predicting key events in the popularity evolution of online information. PloS One, 12(1), e0168749.
   PubMed Web of Science ®Google Scholar
• Hua, M., Han, Z., Chen, S., Yang, M., Zhou, R., & Hu, S. (2014). Late positive potential (LPP) modulation during affective picture processing in preschoolers. Biological Psychology, 101, 77–81.
   PubMed Web of Science ®Google Scholar
• Kalish, M. I., Griffiths, T. L., & Lewandowsky, S. (2007). Iterated learning: Intergenerational knowledge transmission reveals inductive biases. Psychonomic Bulletin & Review, 14(2), 288.
   PubMed Web of Science ®Google Scholar
• Keil, A., Muller, M. M., Gruber, T., Wienbruch, C., Stolarova, M., & Elbert, T. (2001). Effects of emotional arousal in the cerebral hemispheres: A study of oscillatory brain activity and event-related potentials. Clinical Neurophysiology, 112, 2057–2068.
   PubMed Web of Science ®Google Scholar
• Kemp, A. H., Gray, M. A., Eide, P., Silberstein, R. B., & Nathan, P. J. (2002). Steady-state visually evoked potential topography during processing of emotional valence in healthy subjects. Neuroimage, 17(4), 1684–1692.
   PubMed Web of Science ®Google Scholar
• Lasswell, H. D. (1948). The structure and function of communication in society. Communication Ideas, 24, 215–228.
   Google Scholar
• Luo, J., Pan, X., Wang, S., & Huang, Y. (2019). Identifying target audience on enterprise social network. Industrial Management & Data Systems, 46(4), 406–420.
   Google Scholar
• Ma, Q., Shen, Q., Xu, Q., Li, D., Shu, L., & Weber, B. (2011). Empathic responses to others’ gains and losses: An electrophysiological investigation. NeuroImage, 54(3), 2472–2480.
   PubMed Web of Science ®Google Scholar
• McNamara, T. P. (2005). Semantic priming: Perspectives from memory and word recognition. New York, NY: Psychology Press.
   Google Scholar
• Mehrabian, A. (1996). Pleasure-arousal-dominance: A general framework for describing and measuring individual differences in temperament. Current Psychology, 14, 261–292.
   Web of Science ®Google Scholar
• Meyer, D. E., & Schvaneveldt, R. W. (1971). Facilitation in recognizing pairs of words: Evidence of a dependence between retrieval operations. Journal of Experimental Psychology, 90(2), 227–234.
   PubMedGoogle Scholar
• Montag, C., Duke, E., & Markowetz, A. (2016). Toward Psychoinformatics: Computer science meets psychology. Computational and Mathematical Methods in Medicine, 2016, 2983685.
   PubMedGoogle Scholar
• Neely, J. H., & Keefe, D. E. (1989). Semantic context effects on visual word processing: A hybrid prospective/retrospective processing theory. The Psychology of Learning and Motivation, 24, 207–248.
   Google Scholar
• Perez-Osorio, J., Muller, H. J., & Wykowska, A. (2017). Expectations regarding action sequences modulate electrophysiological correlates of the gaze-cueing effect. Psychophysiology, 54(7), 942–954.
   PubMed Web of Science ®Google Scholar
• Reece, A. G., Reagan, A. J., Lix, K. L. M., Dodds, P. S., Danforth, C. M., & Langer, E. J. (2017). Forecasting the onset and course of mental illness with Twitter data. Scientific Reports, 7, 13006.
   PubMed Web of Science ®Google Scholar
• Salas-Zárate, M. D. P., Medina-Moreira, J., Lagos-Ortiz, K., Luna-Aveiga, H., Rodríguez-García, M. Á., & Valencia-García, R. (2017). Sentiment analysis on tweets about diabetes: An aspect-level approach. Computational and Mathematical Methods in Medicine, 2017, 5140631.
   PubMedGoogle Scholar
• Wang, B., Huang, Y., Wu, X., & Li, X. (2015). A fuzzy computing model for identifying polarity of Chines sentiment words. Computational Intelligence and Neuroscience, 2015, 525437.
   PubMedGoogle Scholar
• Wang, C., Zhou, Z., Jin, X., Fang, Y., & Lee, M. K. O. (2017). The influence of affective cues on positive emotion in predicting instant information sharing on microblogs: Gender as a moderator. Information Processing & Management, 53, 721–734.
   Web of Science ®Google Scholar
• Wang, X., Huang, Y., Ma, Q., & Li., N. (2012). Event-related potential P2 correlates of implicit aesthetic experience. Neuroreport, 23(14), 862–866.
   PubMed Web of Science ®Google Scholar
• Yarkoni, T. (2012). Psychoinformatics: New horizons at the interface of the psychological and computing sciences. Current Directions in Psychological Science, 21(6), 391–397.
   Web of Science ®Google Scholar
• Yeung, N., Holroyd, C. B., & Cohen, J. D. (2005). ERP correlates of feedback and reward processing in the presence and absence of response choice. Cerebral Cortex, 15(5), 535–544.
   PubMed Web of Science ®Google Scholar