Central Concerns and Questions

As one of the most exciting trends in computing today, consumer generated social media (CGM), including consumer generated contents and consumer online behavior, holds the potential to change how information is accessed and presented, how knowledge is processed and extracted, and how business is conducted. CGM can affect user adoption, sellers' pricing policies and the nature of competition, vendors' product design, and search engine's advertising. Organizations have adopted blogs to enable the two-way communication between the firms and the consumers to unleash value inside the consumer opinions. With the pervasiveness and rapid growth of mobile and wireless devices, the access availability of consumer generated media continues to accelerate in amount, variety, and scale.

The idea of better serving customer needs is rooted in the age-old notion of listening to the customer to co-create products and services. It is widely recognized today that companies that can better understand their customers' needs will thrive in the competitive landscape. However, the richness and magnitude of today's online consumer generated media have created significant challenges in extracting meaningful information that is embedded in all these contents. We argue that it is crucial and timely to develop a systematic framework to understand the nature of such consumer generated media. The ultimate goal of our research is to develop a methodical approach and a systematic framework for understanding and exploiting the power of consumer generated media in terms of their impact on business, government, and consumers by combining tools from econometric methods, social computing models, and multimedia and text mining techniques.

Emerging Ideas and Initiatives

With the increasingly importance of CGM, our first goal is to understand the economic impact of CGM. This includes comparing the content of these new generated media to traditional media to understand the quality and credibility of the contribution, and examine the cognitive processes of end-consumers to see how they combine these new media with traditional media to make purchase decisions.

• Online information quality
• Online reputation manipulation
• Online consumer sentiment mining

Selected Publications

[1] Nan Hu, Ling Liu, and Jennifer Zhang. Do online Reviews Affect Product Sales? The Role of Reviewer Characteristics and Temporal Effects. Forthcoming Information Technology and Management (IT&M), 2008.

[2] Nan HU, Pavlou PAUL, and Jennifer ZHANG. Overcoming the J-shaped Distribution of Product Reviews. Forthcoming in Communications of the ACM, 2008.

Projects, Presentations and Posters

1. Nan Hu, Bin Chen, and Ling Liu. Are Online Reviews just Noise? The truth, the whole truth, or only the partial truth?
2. Nan Hu, Bin Chen, and Ling Liu. Double Learning or Double Blinding - An investigation of vendor private information acquisition and consumer learning?
3. Nan Hu, Noi Sian Kou, and Vallabh Sambamurthy. The value implication of online consumer reviews.
4. Nan HU, Ling LIU, and Arindam TRIPATHY. Is Blog Value Relevant. American Accounting Association Mid-Year Conference-AIET Section, 01/2008, Redondo Beach.
5. Nan HU, Ling LIU, Jialie SHEN, and Bing CHEN. How to Influence My Customers? The Impact of Electronic Market Design. 17th International World Wide Web Conference (WWW'08), Poster Track, 04/2008.