Research in Social Media: Data Sources and Methodologies

This paper examines both the opportunities and limitations in the use of social media for accounting research. Given the dynamic nature of social media and the richness of the context, there are opportunities for researchers to directly observe communication and information exchanges, typically within the context of an observable social network. The paper provides an overview of the characteristics of four commonly used social network sites (SNSs): Facebook, Twitter, LinkedIn, and StockTwits. The data collection details, opportunities, and limitations are set out. The paper also provides illustrative examples of codes that a researcher might employ to extract information from the SNSs. To provide a comparison of accounting-relevant interactions, the paper measures the extent of posts on StockTwits, Twitter, and Facebook for a random sample of corporate announcements.

[1]  Fiona Fui-Hoon Nah,et al.  Efficacy of Social Media Utilization by Public Accounting Firms: Findings and Directions for Future Research , 2015, J. Inf. Syst..

[2]  Vernon J. Richardson,et al.  Investor Attention and the Pricing of Earnings News , 2014 .

[3]  Ricardo Buettner,et al.  A Systematic Literature Review of Twitter Research from a Socio-Political Revolution Perspective , 2016, 2016 49th Hawaii International Conference on System Sciences (HICSS).

[4]  Jorge Gonçalves,et al.  Modeling What Friendship Patterns on Facebook Reveal About Personality and Social Capital , 2014, ACM Trans. Comput. Hum. Interact..

[5]  Stephen C. Wingreen,et al.  Transferability of Knowledge, Skills, and Abilities Along IT Career Paths: An Agency Theory Perspective , 2010, J. Organ. Comput. Electron. Commer..

[6]  Yi Sun,et al.  Does social climate matter? On friendship groups in social commerce , 2016, Electron. Commer. Res. Appl..

[7]  Shumin Zhai Editorial: TOCHI turns twenty , 2014, TCHI.

[8]  Michael Grossniklaus,et al.  An evaluation of the run-time and task-based performance of event detection techniques for Twitter , 2015, Inf. Syst..

[9]  Fiona H. Rohde,et al.  XBRL Diffusion in Social Media: Discourses and Community Learning , 2015, J. Inf. Syst..

[10]  Adel M. Aladwani Facilitators, characteristics, and impacts of Twitter use: Theoretical analysis and empirical illustration , 2015, Int. J. Inf. Manag..

[11]  Gang Wang,et al.  Crowd Wisdom: The Impact of Opinion Diversity and Participant Independence on Crowd Performance , 2016, AMCIS.

[12]  Robert E. Crossler,et al.  I'm Game, are You? Reducing Real-World Security Threats by Managing Employee Activity in Online Social Networks , 2014, J. Inf. Syst..

[13]  Gordon B. Davis,et al.  Academic Data Collection in Electronic Environments: Defining Acceptable Use of Internet Resources , 2006, MIS Q..

[14]  Dionisios N. Sotiropoulos,et al.  A computational model for mining consumer perceptions in social media , 2017, Decis. Support Syst..

[15]  Roger Debreceny,et al.  8-K Filings, Twitter Activities and Stock Market Reactions , 2015 .

[16]  Gregory S. Miller,et al.  The Evolving Disclosure Landscape: How Changes in Technology, the Media, and Capital Markets Are Affecting Disclosure: the evolving disclosure landscape , 2015 .

[17]  Jian Xu,et al.  Social network user influence sense-making and dynamics prediction , 2014, Expert Syst. Appl..

[18]  Weiguo Fan,et al.  Social Media Adoption and Corporate Disclosure , 2015, J. Inf. Syst..

[19]  France Bélanger,et al.  The Value of Social Media for Small Businesses , 2014, J. Inf. Syst..

[20]  Anja Bechmann,et al.  Using APIs for Data Collection on Social Media , 2014, Inf. Soc..

[21]  José van Dijck,et al.  Users like you? Theorizing agency in user-generated content , 2009 .

[22]  David Cornforth,et al.  Ranking of high-value social audiences on Twitter , 2016, Decis. Support Syst..

[23]  Viviane Pereira Moreira,et al.  Using information retrieval for sentiment polarity prediction , 2016, Expert Syst. Appl..

[24]  Johannes Kuo-Huie Chiang,et al.  Self-presentation and hiring recommendations in online communities: Lessons from LinkedIn , 2015, Comput. Hum. Behav..

[25]  Pasquale De Meo,et al.  On Facebook, most ties are weak , 2012, Commun. ACM.

[26]  Gregory D. Saxton New Media and External Accounting Information: A Critical Review: New Media and External Accounting Information , 2012 .

[27]  Pauli Miettinen,et al.  MDL4BMF: Minimum Description Length for Boolean Matrix Factorization , 2014, TKDD.

[28]  Tawei Wang,et al.  Corporate Network Centrality Score: Methodologies and Informativeness , 2017, J. Inf. Syst..

[29]  Hui Du,et al.  Do Social Media Matter? Initial Empirical Evidence , 2015, J. Inf. Syst..

[30]  V. Kumar,et al.  Practice Prize Winner - Creating a Measurable Social Media Marketing Strategy: Increasing the Value and ROI of Intangibles and Tangibles for Hokey Pokey , 2013, Mark. Sci..

[31]  Mohd Anwar,et al.  Mutual-friend based attacks in social network systems , 2013, Comput. Secur..

[32]  Amy P. Hutton,et al.  The Role of Social Media in the Capital Market: Evidence from Consumer Product Recalls , 2015 .

[33]  David Godes,et al.  Introduction to the Special Issue - Social Media and Business Transformation: A Framework for Research , 2013, Inf. Syst. Res..

[34]  Matthew S. Gerber,et al.  Predicting crime using Twitter and kernel density estimation , 2014, Decis. Support Syst..

[35]  Alessandro Acquisti,et al.  Silent Listeners: The Evolution of Privacy and Disclosure on Facebook , 2013, J. Priv. Confidentiality.

[36]  M. Haas,et al.  Which Problems to Solve? Online Knowledge Sharing and Attention Allocation in Organizations , 2014 .

[37]  Fabio Giglietto,et al.  The Open Laboratory: Limits and Possibilities of Using Facebook, Twitter, and YouTube as a Research Data Source , 2012 .

[38]  Andrea Back,et al.  The dark side of social networking sites: Understanding phishing risks , 2016, Comput. Hum. Behav..

[39]  Matthew A. Russell,et al.  Mining the Social Web: Data Mining Facebook, Twitter, LinkedIn, Google+, GitHub, and More , 2018 .

[40]  Tawei Wang,et al.  The Association between XBRL Adoption and Market Reactions to Earnings Surprises , 2015, J. Inf. Syst..

[41]  Pradeep K. Atrey,et al.  Personality assessment using multiple online social networks , 2015, Multimedia Tools and Applications.

[42]  Tawei Wang,et al.  How Do Investor Relations Related Disclosures on Facebook Contribute to a Company's Information Environment? , 2016, 2016 49th Hawaii International Conference on System Sciences (HICSS).

[43]  Tawei Wang,et al.  Momentum in Social Media and Offline Car Sales after Automobile Recalls , 2016, ICIS.

[44]  Gregory D. Saxton,et al.  New Media and External Accounting Information: A Critical Review , 2012 .

[45]  Paulo Cortez,et al.  Stock market sentiment lexicon acquisition using microblogging data and statistical measures , 2016, Decis. Support Syst..

[46]  Jure Leskovec,et al.  Discovering social circles in ego networks , 2012, ACM Trans. Knowl. Discov. Data.

[47]  Jiawei Han,et al.  Latent Community Topic Analysis: Integration of Community Discovery with Topic Modeling , 2012, TIST.

[48]  Sameena Shah,et al.  Stock Prediction Using Event-Based Sentiment Analysis , 2013, 2013 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT).

[49]  Gregory J. Park,et al.  Psychological Language on Twitter Predicts County-Level Heart Disease Mortality , 2015, Psychological science.

[50]  Gregory S. Miller,et al.  The Role of Dissemination in Market Liquidity: Evidence from Firms' Use of Twitter , 2013 .

[51]  Mohammad Karim Sohrabi,et al.  A comprehensive study on the effects of using data mining techniques to predict tie strength , 2016, Comput. Hum. Behav..

[52]  Athanasios V. Vasilakos,et al.  Revealing the efficiency of information diffusion in online social networks of microblog , 2015, Inf. Sci..

[53]  Daniel E. O'Leary,et al.  KPMG Knowledge Management and the Next Phase: Using Enterprise Social Media , 2016 .

[54]  Kurt Hornik,et al.  Making friends and communicating on Facebook: Implications for the access to social capital , 2014, Soc. Networks.

[55]  Estevam R. Hruschka,et al.  Tweet sentiment analysis with classifier ensembles , 2014, Decis. Support Syst..

[56]  Jonathan Grudin,et al.  When social networks cross boundaries: a case study of workplace use of facebook and linkedin , 2009, GROUP.

[57]  Gregory D. Saxton,et al.  Twittering change: The institutional work of domain change in accounting expertise , 2015 .

[58]  Gregory S. Miller,et al.  The Evolving Disclosure Landscape: How Changes in Technology, the Media, and Capital Markets Are Affecting Disclosure , 2015 .

[59]  Francesc Sebé,et al.  Endorsement deduction and ranking in social networks , 2016, Comput. Commun..

[60]  Wei Zhang,et al.  Has microblogging changed stock market behavior? Evidence from China , 2016 .

[61]  George R. Milne,et al.  Should tweets differ for B2B and B2C? An analysis of Fortune 500 companies' Twitter communications , 2014 .

[62]  G. George,et al.  Corporate Social Responsibility: An Overview and New Research Directions Thematic Issue on Corporate Social Responsibility , 2016 .

[63]  Yahui An,et al.  Celebrities and ordinaries in social networks: Who knows more information? , 2017 .

[64]  Maria Prokofieva,et al.  Twitter-Based Dissemination of Corporate Disclosure and the Intervening Effects of Firms' Visibility: Evidence from Australian-Listed Companies , 2015, J. Inf. Syst..

[65]  Robert E. Crossler,et al.  Voluntary Disclosures via Social Media and the Role of Comments , 2015, J. Inf. Syst..

[66]  Roger S. Debreceny Social Media, Social Networks, and Accounting , 2015, J. Inf. Syst..

[67]  Nuno Horta,et al.  Expert Systems With Applications , 2022 .

[68]  Solitario Exploration,et al.  UNITED STATES SECURITIES AND EXCHANGE COMMISSION Washington, D.C. 20549 FORM 10-K , 2006 .

[69]  Lindsay T. Graham,et al.  A Review of Facebook Research in the Social Sciences , 2012, Perspectives on psychological science : a journal of the Association for Psychological Science.