[Objective] This study explores the key factors that influence the investment decision-making behaviors of rewarded crowdfunding users. [Methods] First, we applied psychological distance theory to define text emotional distance and its three dimensions. Then, we developed a measurement index for the distance based on text analysis. Third, we constructed an econometric model to investigate the influence of text emotional distance on user’s investment decisions. Finally, we conducted an empirical analysis with 161,279 project-descriptions from Kickstarter. [Results] The positive emotional tendency, affinity and interactivity of the texts have significant positive impacts on the users’ investment decisions. Negative emotional tendency poses significant negative effects on investors. Influences of text emotional distance change with different project categories. [Limitations] Findings from our study may not be applied to other crowdfunding business. Also, the qualitative research on text language in psychology and sociology is limited due to technical issues. [Conclusions] The rewarded crowdfunding projects could improve their financing rates with positive emotional tendency and affinity in their descriptions.
( Zeng Jianghong, Chen Siqi. Relationship Between Value Co-Creation and Satisfaction of the Project Supporters: An Study in the Context of Crowd-Funding[J]. Chinese Journal of Management, 2016,13(9):1383-1391.)
[3]
Haas P, Scheiner C, Witt M, et al. Der Einfluss von Gamification auf die Empfundene Selbstwirksamkeit von Teilnehmern von Online-Ideengenerierungswettbewerben über die Zeit[C]// Proceedings of Lecture Notes in Informatics, Gesellschaft für Informatik. 2012.
[4]
Bretschneider U, Leimeister J M. Not Just an Ego-Trip: Exploring Backers’ Motivation for Funding in Incentive-Based Crowdfunding[J]. The Journal of Strategic Information Systems, 2017,26(4):246-260.
doi: 10.1016/j.jsis.2017.02.002
[5]
Zhao Q, Chen C D, Wang J L, et al. Determinants of Backers’ Funding Intention in Crowdfunding: Social Exchange Theory and Regulatory Focus[J]. Telematics and Informatics, 2017,34(1):370-384.
doi: 10.1016/j.tele.2016.06.006
[6]
Du Q Z, Fan W G, Qiao Z L, et al. Money Talks: A Predictive Model on Crowdfunding Success Using Project Description[C]// Proceedings of Americas Conference on Information Systems. 2015.
[7]
Bi S, Liu Z, Usman K. The Influence of Online Information on Investing Decisions of Reward-Based Crowdfunding[J]. Journal of Business Research, 2017,71:10-18.
doi: 10.1016/j.jbusres.2016.10.001
( Yao Zhuo, Chen Xiaohong, Zhang Xi, et al. Research of Factors in Crowd Funding Financing Based on Quality Signal Theory[J]. Financial Economics Research, 2016,31(4):60-71.)
[9]
Thies F, Wessel M, Benlian A. Understanding the Dynamic Interplay of Social Buzz and Contribution Behavior Within and Between Online Platforms-Evidence from Crowdfunding[C]// Proceedings of International Conference on Information Systems, 2014.
[10]
Kang L, Jiang Q, Tan C H. Remarkable Advocates: An Investigation of Geographic Distance and Social Capital for Crowdfunding[J]. Information & Management, 2017,54(3):336-348.
doi: 10.1016/j.im.2016.09.001
[11]
Müllerleile T, Joenssen D W. Key Success-Determinants of Crowdfunded Projects: An Exploratory Analysis[A]//Data Science, Learning by Latent Structures, and Knowledge Discovery[M]. Springer, 2015: 271-281.
[12]
Parhankangas A, Renko M. Linguistic Style and Crowdfunding Success Among Social and Commercial Entrepreneurs[J]. Journal of Business Venturing, 2017,32(2):215-236.
doi: 10.1016/j.jbusvent.2016.11.001
[13]
Wang W, Zhu K, Wang H W, et al. The Impact of Sentiment Orientations on Successful Crowdfunding Campaigns through Text Analytics[J]. IET Software, 2017,11(5):229-238.
doi: 10.1049/sfw2.v11.5
( Wang Wei, Chen Wei, Zhu Xiaoguo, et al. Success Rate of Crowdfunding and Persuasion of Language Style -An Empirical Study Based on Kickstarter[J]. Management World, 2016(5):81-98.)
[15]
Chung S, Park J. Exploring Consumer Evaluations in Social Media: The Role of Psychological Distance Between Company and Consumer[J]. Computers in Human Behavior, 2017,76:312-320.
doi: 10.1016/j.chb.2017.07.042
[16]
Lim S, Cha S Y, Park C, et al. Getting Closer and Experiencing Together: Antecedents and Consequences of Psychological Distance in Social Media-Enhanced Real-Time Streaming Video[J]. Computers in Human Behavior, 2012,28(4):1365-1378.
doi: 10.1016/j.chb.2012.02.022
[17]
Fiedler K. Construal Level Theory as an Integrative Framework for Behavioral Decision-Making Research and Consumer Psychology[J]. Journal of Consumer Psychology, 2007,17(2):101-106.
doi: 10.1016/S1057-7408(07)70015-3
[18]
Larsen R J, Diener E. Affect Intensity as an Individual Difference Characteristic: A Review[J]. Journal of Research in Personality, 1987,21(1):1-39.
doi: 10.1016/0092-6566(87)90023-7
[19]
Dickert S, Sagara N, Slovic P. Affective Motivations to Help Others: A Two-Stage Model of Donation Decisions[J]. Journal of Behavioral Decision Making, 2011,24(4):361-376.
doi: 10.1002/bdm.v24.4
[20]
Huang Y L, Starbird K, Orand M, et al. Connected Through Crisis: Emotional Proximity and the Spread of Misinformation Online[C]//Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work & Social Computing. Vancouver, BC, Canada: ACM Press, 2015: 969-980.
[21]
Marcin M, Kristian H. Shine Bright like a Diamond-Exploring the Effects of Online-Product Presentation on Backing Behavior in Reward-Based Crowdfunding[C]// Proceedings of the 23rd European Conference on Information Systems. 2015.
[22]
Vismara S. Information Cascades among Investors in Equity Crowdfunding [C]//Proceedings of Academy of Management Annual Meeting, 2015: 11519.
[23]
Liu Q, Feng C, Huang H. Emotional Tendency Identification for Micro-blog Topics Based on Multiple Characteristics[C]// Proceedings of the 26th Pacific Asia Conference on Language, Information, and Computation. 2012: 280-288.
[24]
Abe J A A. Changes in Alan Greenspan’s Language Use Across the Economic Cycle: A Text Analysis of His Testimonies and Speeches[J]. Journal of Language and Social Psychology, 2011,30(2):212-223.
doi: 10.1177/0261927X10397152
[25]
Page R. Interactivity and Interaction: Text and Talk in Online Communities[A]//Intermediality and Storytelling[M]. De Gruyter, 2011.
[26]
Warnick B, Xenos M, Endres D, et al. Effects of Campaign-to-User and Text-Based Interactivity in Political Candidate Campaign Web Sites[J]. Journal of Computer-Mediated Communication, 2005,10(3). DOI: 10.1111/j.1083-6101.2005.tb00253.x.
[27]
Endres D, Warnick B. Text‐Based Interactivity in Candidate Campaign Web Sites: A Case Study from the 2002 Elections[J]. Western Journal of Communication, 2004,68(3):322-342.
doi: 10.1080/10570310409374804
[28]
Kemp E, Kennett-Hensel P A, Kees J . Pulling on the Heartstrings: Examining the Effects of Emotions and Gender in Persuasive Appeals[J]. Journal of Advertising, 2013,42(1):69-79.
doi: 10.1080/00913367.2012.749084
( Wang Ying, Gong Huaping. Analysis of Sentiment Tendency of Big Data Online Public Opinion Based on the Sentiment Dimension——Taking “the Independent Cleaning of Nanchang University” Weibo Public Opinion Event as an Example[J]. Information Science, 2017,35(4):37-42.)
[30]
Kahneman D A, Tversky A N. Prospect Theory: An Analysis of Decision Under Risk[J]. Econometrica, 2013,47(2):263-291.
doi: 10.2307/1914185
[31]
Kim J, Gupta P. Emotional Expressions in Online User Reviews: How They Influence Consumers’ Product Evaluations[J]. Journal of Business Research, 2012,65(7):985-992.
doi: 10.1016/j.jbusres.2011.04.013
[32]
Folkes V S. Recent Attribution Research in Consumer Behavior: A Review and New Directions[J]. Journal of Consumer Research, 1988,14(4):548-565.
doi: 10.1086/jcr.1988.14.issue-4
[33]
Pennebaker J W, Mehl M R, Niederhoffer K G. Psychological Aspects of Natural Language Use: Our Words, Our Selves[J]. Annual Review of Psychology, 2003,54(1):547-577.
doi: 10.1146/annurev.psych.54.101601.145041
[34]
Campbell R S, Pennebaker J W. The Secret Life of Pronouns: Flexibility in Writing Style and Physical Health[J]. Psychological Science, 2003,14(1):60-65.
doi: 10.1111/1467-9280.01419
[35]
Sexton J B, Helmreich R L. Analyzing Cockpit Communication: The Links Between Language, Performance, Error, and Workload[J]. Human Performance in Extreme Environments, 2000,5(1):63-68.
[36]
Tausczik Y R, Pennebaker J W. The Psychological Meaning of Words: LIWC and Computerized Text Analysis Methods[J]. Journal of Language and Social Psychology, 2010,29(1):24-54.
doi: 10.1177/0261927X09351676
[37]
Taboada M, Brooke J, Tofiloski M, et al. Lexicon-Based Methods for Sentiment Analysis[J]. Computational Linguistics, 2011,37(2):267-307.
doi: 10.1162/COLI_a_00049
[38]
Chu C H, Roopa A H, Chang Y C, et al. Constructing Sentiment Sensitive Vectors for Word Polarity Classification[C]// Proceedings of 2015 Conference on Technologies and Applications of Artificial Intelligence (TAAI). 2015: 252-259.
[39]
Basiri M E, Kabiri A. Translation is not Enough: Comparing Lexicon-Based Methods for Sentiment Analysis in Persian[C]//Proceedings of 2017 International Symposium on Computer Science and Software Engineering Conference (CSSE). IEEE, 2017: 36-41.
[40]
Hu M Q, Liu B. Mining and Summarizing Customer Reviews[C]// Proceedings of the 10th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 2004: 168-177.
[41]
Subrahmanian V S, Reforgiato D. AVA: Adjective-Verb-Adverb Combinations for Sentiment Analysis[J]. IEEE Intelligent Systems, 2008,23(4):43-50.
doi: 10.1109/MIS.2008.57
[42]
Kennedy A, Inkpen D. Sentiment Classification of Movie Reviews Using Contextual Valence Shifters[J]. Computational Intelligence, 2006,22(2):110-125.
doi: 10.1111/coin.2006.22.issue-2
[43]
Gunsch M A, Brownlow S, Haynes S E, et al. Differential Forms Linguistic Content of Various of Political Advertising[J]. Journal of Broadcasting & Electronic Media, 2000,44(1):27-42.
[44]
Cruz R E, Leonhardt J M, Pezzuti T. Second Person Pronouns Enhance Consumer Involvement and Brand Attitude[J]. Journal of Interactive Marketing, 2017,39:104-116.
doi: 10.1016/j.intmar.2017.05.001
[45]
Martínez-Cámara E, Martín-Valdivia M T, Ureña-López L A , et al. Sentiment Analysis in Twitter[J]. Natural Language Engineering, 2014,20(1):1-28.
doi: 10.1017/S1351324912000332
[46]
Scheaf D J, Davis B C, Webb J W, et al. Signals’ Flexibility and Interaction with Visual Cues: Insights from Crowdfunding[J]. Journal of Business Venturing, 2018,33(6):720-741.
doi: 10.1016/j.jbusvent.2018.04.007
[47]
Kim P H, Buffart M, Croidieu G. TMI: Signaling Credible Claims in Crowdfunding Campaign Narratives[J]. Group & Organization Management, 2016,41(6):717-750.
( Dai Jing, Ye Cuihong, Chen Yiguo, et al. Effect of Quality Signal on Investment Decision in Reward Crowdfunding——Evidence from Jingdong Reward Crowdfunding Platform[J]. Chinese Review of Financial Studies, 2016(3):53-66.)
[49]
Park H J, Dhandra T K. Relation Between Dispositional Mindfulness and Impulsive Buying Tendency: Role of Trait Emotional Intelligence[J]. Personality and Individual Differences, 2017,105:208-212.
doi: 10.1016/j.paid.2016.09.061
