The DOI matches its Crossref record; 38 of the 38 references it cites were found in a registry or an index.
Spreading Social Media Messages on Facebook: An Analysis of Restaurant Business-to-Consumer Communications
Abstract
As a method of determining what types of social media messages work best for hospitality firms, this study examined what types of messages gained the most clicks of “Like” and comments on Facebook. An analysis of the number of likes and comments regarding nine hundred and eighty-two Facebook messages from ten restaurant chains and two independent operators revealed clear patterns. The more popular keywords involved information about the restaurant (e.g., menu descriptions) and the less popular messages were those that contained marketing-related words (including “winner” and “check”). Dividing the messages into four media types, namely, status (text only), link (containing a URL), video (embedding a video), and photo (showing photos), revealed that photo and status receive more likes and comments than the other two categories. Social media messages can also be categorized into two message types: sales and marketing (about two-thirds of the messages in this study) and conversational messages. Based on number of likes and comments, conversational messages are endorsed by more Facebook users. Finally, cross-effects of media type and message type affect the number of comments a message received. Although these results do not expressly assess Facebook users’ reactions, the guidelines developed here should help managers improve their use of Facebook, as well as provide groundwork for developing a defined typology of Facebook messages and an automatic text classifier with the machine learning techniques.
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Cites
A Coefficient of Agreement for Nominal Scales
Cohen, J. (1960) · Educational and Psychological Measurement · doi:10.1177/001316446002000104 · Cited by 42,398
Users of the world, unite! The challenges and opportunities of Social Media
Kaplan, A. M., & Haenlein, M. (2010) · Business Horizons · doi:10.1016/j.bushor.2009.09.003 · Cited by 17,875
Text categorization with Support Vector Machines: Learning with many relevant features
Joachims, T. (1998) · Lecture Notes in Computer Science · doi:10.1007/bfb0026683 · Cited by 7,999
Social media: The new hybrid element of the promotion mix
Mangold, W. G., & Faulds, D. J. (2009) · Business Horizons · doi:10.1016/j.bushor.2009.03.002 · Cited by 4,111
Buhalis, D., & Law, R. (2008) · Tourism Management · doi:10.1016/j.tourman.2008.01.005 · Cited by 3,823 · cited 1×
“…and Runyan 2012), even though managers and scholars in the hospitality, travel, and tourism industries have urged that social media should become a top priority for future research (e.g., Buhalis and Law 2008; Dev, Buschman, and Bowen 2010; Line and Runyan 2012; Williams, Stewart, and Larsen 2012).”
BackgroundRole of social media in online travel information search
Xiang, Z., & Gretzel, U. (2010) · Tourism Management · doi:10.1016/j.tourman.2009.02.016 · Cited by 3,274
Electronic word-of-mouth in hospitality and tourism management
Litvin, S. W., Goldsmith, R. E., & Pan, B. (2008) · Tourism Management · doi:10.1016/j.tourman.2007.05.011 · Cited by 3,267
The Impact of New Media on Customer Relationships
Hennig-Thurau, T., Malthouse, E. C., Friege, C., Gensler, S., Lobschat, L., Rangaswamy, A., & Skiera, B. (2010) · Journal of Service Research · doi:10.1177/1094670510375460 · Cited by 1,406
The social media bible: tactics, tools, and strategies for business success
(2009) · Choice Reviews Online · doi:10.5860/choice.47-0374 · Cited by 796
Socialnomics: how social media transforms the way we live and do business
(2010) · Choice Reviews Online · doi:10.5860/choice.48-1576 · Cited by 752
Cited by
Progress on information and communication technologies in hospitality and tourism
Law, R., Buhalis, D., & Cobanoglu, C. (2014) · International Journal of Contemporary Hospitality Management · doi:10.1108/ijchm-08-2013-0367 · Cited by 748
Mariani, M. M., Perez‐Vega, R., & Wirtz, J. (2022) · Psychology & Marketing · doi:10.1002/mar.21619 · Cited by 631
Odoom, R., Anning-Dorson, T., & Acheampong, G. (2017) · Journal of Enterprise Information Management · doi:10.1108/jeim-04-2016-0088 · Cited by 267
Metadata
- Authors
- Kwok, L., & Yu, B.
- Venue
- Cornell Hospitality Quarterly
- Publisher
- SAGE Publications
- Published
- 2012-09-24
- Volume
- 54
- Issue
- 1
- Pages
- 84-94
- ISSN
- 1938-9655 (ISSN-L)
- 1938-9663
- OpenAlex
- W2029776915
- Cited by
- 337
- References
- 38
- FWCI
- 43.35
- Type
- journal article
- Language
- en
- Open access
- closed
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