research-article

When daily deal services meet Twitter: understanding Twitter as a daily deal marketing platform

Authors:

Jaimie Y. Park,

Chin-Wan ChungAuthors Info & Claims

WebSci '12: Proceedings of the 4th Annual ACM Web Science Conference

Pages 233 - 242

https://doi.org/10.1145/2380718.2380748

Published: 22 June 2012 Publication History

Abstract

Twitter, a microblogging service which enables users to build social networks and share information, has been recognized as a potentially powerful marketing platform. Daily deal service is one of the many types of businesses that leverage Twitter for marketing purpose; daily deal providers such as Groupon and LivingSocial are not only engaged in active interactions with their potential customers on Twitter but are also encouraging the customers to participate in advertising products through Twitter. Despite the recent surge of interest in studying Twitter as a medium of information diffusion, little is understood about the daily deal information sharing behavior on Twitter. In this research we pose following questions: what kind of daily deals are being talked about in Twitter, when, and how? In order to answer these questions we crawl and analyze a large-scale Twitter and Groupon data to understand the characteristics of the user-generated tweets containing the URL links to daily deals. We also examine the relationship between the sharing of tweets and the actual sales performance of the daily deal service based on the data collected from LivingSocial. We discover the demands of users reflected through Twitter and characterize the customers' information sharing patterns across Twitter. Further, we provide evidence that sharing daily deals on Twitter contributes to the improved sales performance. These findings shed light on the significance of Twitter as a marketing platform, providing key insights for businesses to consider in formulating social marketing strategies.

References

[1]

Ahn, J., et al. Media landscape in Twitter: A World of New Conventions and Political Diversity, in Proceedings of the Fifth International AAAI Conference on Weblogs and Social Media, 2011.

[2]

Berger, J. A. and E. M. Schwartz, What Do People Talk About? Drivers of Immediate and Ongoing Word-of-Mouth. Journal of Marketing Research, Forthcoming, 2011.

[3]

Chen, Y., S. Fay, and Q. Wang, The Role of Marketing in Social Media: How Online Consumer Reviews Evolve. Journal of Interactive Marketing, 2011.

[4]

Cheng, A., Evans, M., and Singh H. Inside Twitter: An in-Depth Look Inside the Twitter World. Feb 2012; http://www.sysomos.com/insidetwitter/.

[5]

Courtenay Honeycutt, S. C. H., Beyond Microblogging: Conversation and Collaboration via Twitter, in Proceedings of the 42nd Hawaii International Conference on System Sciences, 2009. IEEE Computer Society. p. 1--10.

Digital Library

[6]

Dellarocas, C. N., The Digitization of Word-of-Mouth: Promise and Challenges of Online Feedback Mechanisms. Management Science, 2003.

Digital Library

[7]

Dholakia, U. M., How Effective are Groupon Promotions for Businesses? SSRN eLibrary, 2010.

[8]

Faloutsos, M. et al., On Power-Law Relationships of the Internet Topology. in Proceedings of the Conference on Applications, Technologies, Architectures, and Protocols for Computer Communication, 1999.

Digital Library

[9]

Fisher, D. and P. Dourish, Social and Temporal Structures in Everyday Collaboration, in Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 2004. ACM: Vienna, Austria. p. 551--558.

Digital Library

[10]

Hennig-Thurau et al., Electronic Word-of-Mouth via Consumer-Opinon Platforms: What Motivates Consumers to Articulate Themselves on the Internet? Journal of Interactive Marketing, 2004.: p. 38--52.

[11]

Jansen, B. J., et al., Twitter Power: Tweets as Electronic Word of Mouth. Journal of the American Society for Information Science and Technology, 2009.

Digital Library

[12]

Java, A., et al., Why We Twitter: Understanding Microblogging Usage and Communities, in Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 Workshop on Web Mining and Social Network Analysis, 2007. ACM: San Jose, California. p. 56--65.

Digital Library

[13]

John Byers, M. M.a.G.Z. Daily Deals: Prediction, Social Diffusion, and Reputational Ramifications. in Proceedings of the 20th International Conference on Web Search and Data Mining, 2012. Seattle, Washington, USA.

Digital Library

[14]

Kwak, H., et al., What is Twitter, a Social Network or a News Media?, in Proceedings of the 19th International Conference on World Wide Web, 2010.

Digital Library

[15]

Kwak, H., et al., Fragile Online Relationship: a First Look at Unfollow Dynamics in Twitter, in Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 2011.

Digital Library

[16]

Leskovec, J., L. A. Adamic, and B. A. Huberman, The Dynamics of Viral Marketing. ACM Trans. Web, 2007.

Digital Library

[17]

Lynn, M., Scarcity Effects on Value: A Quantitative Review of the Commodity Theory Literature. Psychology and Marketing, 991. 8(1): p. 43--57.

[18]

Lynn, M., Scarcity Effects on Desirability: Mediated by Assumed Expensiveness? Journal of Economic Psychology, 1989.

[19]

Park, D.-H. and S. Kim, The Effects of Consumer Knowledge on Message Processing of Electronic Word-of-Mouth via Online Consumer Reviews. Electronic Commerce Research and Applications, 2008. 7(4): p. 399--410.

Digital Library

[20]

Phelps, J. E. et al., Viral Marketing or Electronic Word-of-Mouth Advertising: Examining Consumer Responses and Motivations to Pass Along Email. Journal of Advertising Research, 2004.

[21]

Stolfo, S. J., et al., Behavior-Based Modeling and its Application to Email Analysis. ACM Transactions on Internet Technology, 2006. 6(2): p. 187--221.

Digital Library

[22]

Subramani, M. R. and B. Rajagopalan, Knowledge-Sharing and Influence in Online Social Networks via Viral Marketing. Communications of the ACM, 2003. 46(12): p. 300--307.

Digital Library

[23]

Sun, T., et al., Online Word-of-Mouth (or Mouse): An Exploration of Its Antecedents and Consequences. Journal of Computer-Mediated Communication, 2006. 11(4): p. 1104--1127.

[24]

Trusov, M., et al, Effects of Word-of-Mouth versus Traditional Marketing: Findings from an Internet Social Networking Site. SSRN Library, 2008.

[25]

Wirtz, J. and P. Chew, The Effects of Incentives, Deal Proneness, Satisfaction and Tie Strength on Word-of-Mouth Behaviour. International Journal of Service Industry Management, 2002. 13(2): p. 141--162.

[26]

Wu, S., et al., Who Says What to Whom on Twitter, in Proceedings of the 20th International Conference on World Wide Web, 2011. ACM: Hyderabad, India. p. 705--714.

Digital Library

Cited By

Sipos D(2023)A Quantitative Survey of Twitter's Influence on Online BusinessResearch in Social Change10.2478/rsc-2023-000515:1(53-66)Online publication date: 15-Nov-2023
https://doi.org/10.2478/rsc-2023-0005
Goanta CBertaglia TIamnitchi A(2022)The Case for a Legal Compliance API for the Enforcement of the EU’s Digital Services Act on Social Media PlatformsProceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency10.1145/3531146.3533190(1341-1349)Online publication date: 21-Jun-2022
https://dl.acm.org/doi/10.1145/3531146.3533190
Wang CLin YChang HChou S(2020)Consumer Sentiment in Tweets and Coupon Information-Sharing BehaviorInformation Diffusion Management and Knowledge Sharing10.4018/978-1-7998-0417-8.ch041(823-842)Online publication date: 2020
https://doi.org/10.4018/978-1-7998-0417-8.ch041
Show More Cited By

Index Terms

When daily deal services meet Twitter: understanding Twitter as a daily deal marketing platform
1. Applied computing
  1. Law, social and behavioral sciences

Recommendations

A sentiment analysis of audiences on twitter: who is the positive or negative audience of popular twitterers?
ICHIT'11: Proceedings of the 5th international conference on Convergence and hybrid information technology

Microblogging is a new informal communication medium of blogging that differs from a traditional blog in which content is much shorter. Microbloggers post about topics that describe their current status. Twitter is a popular microblogging service and ...
Information resonance on Twitter: watching Iran
SOMA '10: Proceedings of the First Workshop on Social Media Analytics

Twitter has undoubtedly caught the attention of both the general public, and academia as a microblogging service worthy of study and attention. Twitter has several features that sets it apart from other social media/networking sites, including its 140 ...
A comparative study of users' microblogging behavior on sina weibo and twitter
UMAP'12: Proceedings of the 20th international conference on User Modeling, Adaptation, and Personalization

In this article, we analyze and compare user behavior on two different microblogging platforms: (1) Sina Weibo which is the most popular microblogging service in China and (2) Twitter. Such a comparison has not been done before at this scale and is ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

WebSci '12: Proceedings of the 4th Annual ACM Web Science Conference

June 2012

531 pages

ISBN:9781450312288

DOI:10.1145/2380718

Conference Chairs:
Noshir Contractor,
Brian Uzzi,
Program Chairs:
Michael Macy
Cornell University
,
Wolfgang Nejdl
L3S Research Center

Copyright © 2012 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 June 2012

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Funding Sources

Ministry of Education, Science and Technology

Conference

WebSci '12

Sponsor:

SIGWEB

WebSci '12: Web Science 2012

June 22 - 24, 2012

Illinois, Evanston

Acceptance Rates

Overall Acceptance Rate 245 of 933 submissions, 26%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

13
Total Citations
View Citations
755
Total Downloads

Downloads (Last 12 months)11
Downloads (Last 6 weeks)0

Reflects downloads up to 25 Dec 2024

Other Metrics

View Author Metrics

Citations

Cited By

Sipos D(2023)A Quantitative Survey of Twitter's Influence on Online BusinessResearch in Social Change10.2478/rsc-2023-000515:1(53-66)Online publication date: 15-Nov-2023
https://doi.org/10.2478/rsc-2023-0005
Goanta CBertaglia TIamnitchi A(2022)The Case for a Legal Compliance API for the Enforcement of the EU’s Digital Services Act on Social Media PlatformsProceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency10.1145/3531146.3533190(1341-1349)Online publication date: 21-Jun-2022
https://dl.acm.org/doi/10.1145/3531146.3533190
Wang CLin YChang HChou S(2020)Consumer Sentiment in Tweets and Coupon Information-Sharing BehaviorInformation Diffusion Management and Knowledge Sharing10.4018/978-1-7998-0417-8.ch041(823-842)Online publication date: 2020
https://doi.org/10.4018/978-1-7998-0417-8.ch041
Wang CLin YChang HChou S(2017)Consumer Sentiment in Tweets and Coupon Information-Sharing BehaviorInternational Journal of Online Marketing10.4018/IJOM.20170701017:3(1-19)Online publication date: 1-Jul-2017
https://dl.acm.org/doi/10.4018/IJOM.2017070101
Teodorescu HSaharia N(2015)An internet slang annotated dictionary and its use in assessing message attitude and sentiments2015 International Conference on Speech Technology and Human-Computer Dialogue (SpeD)10.1109/SPED.2015.7343084(1-8)Online publication date: Oct-2015
https://doi.org/10.1109/SPED.2015.7343084
Jiawei Chen Hongyan Liu Jun He (2015)Predicting the influence of group buying on the restaurant's popularity by online reviews2015 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)10.1109/FSKD.2015.7382090(1068-1072)Online publication date: Aug-2015
https://doi.org/10.1109/FSKD.2015.7382090
Zhou XWang WJin Q(2015)Multi-dimensional attributes and measures for dynamical user profiling in social networking environmentsMultimedia Tools and Applications10.1007/s11042-014-2230-974:14(5015-5028)Online publication date: 1-Jul-2015
https://dl.acm.org/doi/10.1007/s11042-014-2230-9
Murthy DBowman S(2014)Big Data solutions on a small scale: Evaluating accessible high-performance computing for social researchBig Data & Society10.1177/20539517145591051:2Online publication date: 25-Nov-2014
https://doi.org/10.1177/2053951714559105
Griffin CSquicciarini AStyer S(2014)Identifying multi-regime behaviors of memes in Twitter data2014 Science and Information Conference10.1109/SAI.2014.6918281(827-837)Online publication date: Aug-2014
https://doi.org/10.1109/SAI.2014.6918281
Alfantoukh LDurresi A(2014)Techniques for Collecting data in Social NetworksProceedings of the 2014 17th International Conference on Network-Based Information Systems10.1109/NBiS.2014.92(336-341)Online publication date: 10-Sep-2014
https://dl.acm.org/doi/10.1109/NBiS.2014.92
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents