Please wait a minute...
Data Analysis and Knowledge Discovery  2021, Vol. 5 Issue (4): 60-71    DOI: 10.11925/infotech.2096-3467.2020.0751
Current Issue | Archive | Adv Search |
Studying Investment Decisions of Rewarded Crowdfunding Users with Emotional Distance and Text Analysis
Chen Jun(),Liang Hao,Qian Chen
School of Information Management, Wuhan University, Wuhan 430072, China
Download: PDF (808 KB)   HTML ( 4
Export: BibTeX | EndNote (RIS)      
Abstract  

[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.

Key wordsRewarded Crowdfunding      Investment Decision      Text Analysis      Emotional Distance     
Received: 31 July 2020      Published: 15 December 2020
ZTFLH:  分类号: G203  
Fund:National Natural Science Foundation of China(71871168);Social Science Foundation of Wuhan University
Corresponding Authors: Chen Jun     E-mail: christina_cj@whu.edu.cn

Cite this article:

Chen Jun,Liang Hao,Qian Chen. Studying Investment Decisions of Rewarded Crowdfunding Users with Emotional Distance and Text Analysis. Data Analysis and Knowledge Discovery, 2021, 5(4): 60-71.

URL:

http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2020.0751     OR     http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2021/V5/I4/60

Research Model
词性 r a v n
词条数量 5 580 30 002 25 047 146 312
SWN Key Lexical Statistics
项目类别 项目数量 成功项目
数量
失败项目
数量
项目
成功率
影视 54 322 23 614 30 708 43.4%
艺术 47 911 23 833 24 078 49.7%
设计与科技 51 389 17 107 34 282 33.2%
漫画与插图 10 460 6 111 4 349 58.4%
食品与手工 46 473 13 596 32 877 29.2%
游戏 27 358 12 364 14 994 45.1%
音乐 47 395 26 201 21 194 55.2%
出版 37 017 12 879 24 138 34.7%
总数量统计 322 325 135 705 186 620 42.1%
Project Category Statistics
变量 数据
类型
平均值 标准差 非空
项目数
中位数
筹资目标 数值型 45 107 1 135 032 322 325 5 000
图片数量 数值型 5.75 10.42 321 479 1
对外链接数量 数值型 1.92 4.44 321 479 0
文本长度 数值型 536.17 533.44 322 325 369
是否首次发起 布尔型 - - - -
是否含有视频 布尔型 - - - -
积极情感倾向 数值型 11.00 11.62 322 325 7.40
消极情感倾向 数值型 7.52 111.69 322 325 4.54
文本亲和性 数值型 2.10 2.32 322 325 1.36
文本交互性 数值型 1.47 1.46 322 325 1.13
Variable Mean and Standard Deviation Statistics
变量类型 变量名称 变量代号 变量含义
因变量 投资者人数 BC 项目的投资者数量
控制变量 筹资目标金额 GO 由发起人设立,平台规定实际筹资额不小于筹资目标时项目筹资成功
图片数量 PC 项目说明页面中的图片数量
对外链接数量 HC 项目说明页面中的外部链接数量
文本长度 DEL 项目说明页面描述文本长度
项目(发起人)是否首次发起 IFC 项目发起人是否是首次在平台上发起项目,若是,则值为1,否则值为0
是否含有视频 HV 项目说明页面中是否含有视频介绍,若是,则值为1,否则值为0
自变量 积极情感倾向 POS 文本描述中所代表的积极倾向值
消极情感倾向 NEG 文本描述中所代表的消极倾向值
文本亲和性 AFF 文本描述中的第一人称代词的词频
文本交互性 INT 文本描述中的第二人称代词的词频
Description of Variables
变量 被解释变量:投资者数量
模型1 模型2
系数 T 系数 T
筹资目标 0.060 5*** 27.511 0.058 9*** 26.922
图片数量 0.027 7*** 12.357 0.028 9*** 12.896
对外链接数量 0.072 9*** 33.118 0.069 6*** 31.719
是否首次发起 -0.827 2*** -186.729 -0.819 9*** -186.027
是否含有视频 0.385 5*** 84.802 0.368 3*** 81.165
文本长度 0.125 7*** 53.535 0.152 4*** 36.249
积极倾向情感 0.027 4*** 7.014
消极倾向情感 -0.058 4*** -17.118
文本亲和性 0.083 7*** 39.505
文本交互性 0.004 5** 2.132
截距项 0.200 8*** 44.677 0.207 7*** 46.458
F值 10 770*** 6 741***
R-squared 0.286 0.295
Results of Linear Regression
项目类别 积极情感 消极情感 文本亲和性 文本交互性
影视 0.020 6**
(2.212)
-0.011 3
(-1.406)
0.050 0***
(8.431)
0.017 1**
(2.583)
艺术 -0.017 5**
(-1.909)
-0.016 6**
(-1.939)
0.116 5***
(20.290)
-0.018 5***
(-3.220)
设计与科技 0.018 0**
(1.907)
-0.016 1**
(-1.858)
0.063 6***
(10.322)
-0.011 6***
(-2.904)
漫画与插画 0.029 7
(1.075)
0.008 4
(0.354)
0.067 9***
(3.203)
0.067 9***
(3.546)
食品与手工 8.616e-05
(0.010)
0.017 7**
(2.147)
0.065 5***
(15.810)
-0.003 5
(-0.749)
游戏 0.064 8***
(4.492)
-0.056 1***
(-5.958)
0.016 2*
(1.841)
-0.008 1
(-1.400)
音乐 0.081 1***
(7.028)
-0.019 6*
(-1.691)
0.060 7***
(13.574)
0.057 5***
(10.139)
出版 0.020 8**
(2.130)
-0.016 7**
(-1.989)
0.096 8***
(13.527)
0.001 1
(0.185)
Linear Regression Results for Main Effects of Categories
[1] Mollick E. The Dynamics of Crowdfunding: An Exploratory Study[J]. Journal of Business Venturing, 2014,29(1):1-16.
doi: 10.1016/j.jbusvent.2013.06.005
[2] 曾江洪, 陈斯琪. 众筹模式下项目支持者价值共创与满意度关系研究[J]. 管理学报, 2016,13(9):1383-1391.
[2] ( 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
[8] 姚卓, 陈晓红, 张希, 等. 基于质量信号的众筹融资影响因素研究[J]. 金融经济学研究, 2016,31(4):60-71.
[8] ( 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
[14] 王伟, 陈伟, 祝效国, 等. 众筹融资成功率与语言风格的说服性——基于Kickstarter的实证研究[J]. 管理世界, 2016(5):81-98.
[14] ( 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
[29] 王英, 龚花萍. 基于情感维度的大数据网络舆情情感倾向性分析研究——以“南昌大学自主保洁”微博舆情事件为例[J]. 情报科学, 2017,35(4):37-42.
[29] ( 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.
[48] 戴静, 叶翠红, 陈义国, 等. 质量信号对众筹投资者决策的影响——来自京东商品众筹的证据[J]. 金融评论, 2016(3):53-66.
[48] ( 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
[1] Hyonil Kim,Ou Shiyan. Identifying Citation Texts with Unsupervised Method[J]. 数据分析与知识发现, 2021, 5(1): 66-77.
[2] Tian Zhonglin,Wu Xu,Xie Xiaqing,Xu Jin,Lu Yueming. Real-time Analysis Model for Short Texts with Relationship Graph of Domain Semantics[J]. 数据分析与知识发现, 2020, 4(2/3): 239-248.
[3] Jiang Wu,Yinghui Zhao,Jiahui Gao. Research on Weibo Opinion Leaders Identification and Analysis in Medical Public Opinion Incidents[J]. 数据分析与知识发现, 2019, 3(4): 53-62.
[4] Chengzhi Zhang,Zheng Li. Extracting Sentences of Research Originality from Full Text Academic Articles[J]. 数据分析与知识发现, 2019, 3(10): 12-18.
[5] Yu Yan,Zhao Naixuan. Weighted Topic Model for Patent Text Analysis[J]. 数据分析与知识发现, 2018, 2(4): 81-89.
[6] Ma Tianyi,Zhang Pengzhu,Feng Haoyin. Knowledge Requirement Model for Online Outsourcing Tasks[J]. 现代图书情报技术, 2016, 32(3): 74-81.
  Copyright © 2016 Data Analysis and Knowledge Discovery   Tel/Fax:(010)82626611-6626,82624938   E-mail:jishu@mail.las.ac.cn