Abstract
In a multi-channel online communication environment, dissemination of high quality content to multiple channels is a necessity. With the intention of actively communicating and engaging with the audiences on each channel, content should be disseminated to as many channels as possible. Due to the heterogeneity of channels’ specifications, the challenge is to find the best possible combination of which content should be disseminated to which channel. In this paper we introduce an approach so called publication flow as a structured way of disseminating content to multiple channels. The proposed approach enables multiple channels content dissemination and at the same time maximizes the dissemination main objective of reaching the widest audiences possible. By defining the challenge as a minimum cost flow problem, an optimal publication flow can be achieved by minimizing the costs (technical, effectiveness and social) of disseminating a particular type of content to a particular channel. We employ our approach to analyse and evaluate how content is disseminated to various social media channels within the tourism industry.
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References
Agichtein, E., Castillo, C., Donato, D., Gionis, A., & Mishne, G. (2008). Finding high-quality content in social media. In Proceedings of the 2008 International Conference on Web Search and Data Mining (pp. 183–194). ACM.
Akbar, Z., Garcia, J. M., Toma, I., & Fensel, D. (2015). Measuring the impact of content adaptation on social media engagement. In Proceedings of the 2nd European Conference on Social Media (pp. 1–10). ACPI.
Antaris, S., Rafailidis, D., & Nanopoulos, A. (2014). Link injection for boosting information spread in social networks. Social Network Analysis and Mining, 4(1), 236.
Ariely, D. (2000). Controlling the information flow: Effects on consumers’ decision making and preferences. Journal of Consumer Research, 27(2), 233–248.
Bakhshi, S., Shamma, D. A., & Gilbert, E. (2014). Faces engage us: Photos with faces attract more likes and comments on instagram. In Proceeding of the SIGCHI Conference on Human Factors in Computing Systems (pp. 965–974). ACM.
Bilgihan, A., Okumus, F., Nusair, K., & Bujisic, M. (2014). Online experiences: Flow theory, measuring online customer experience in e-commerce and managerial implications for the lodging industry. Information Technology and Tourism, 14(1), 49–71.
Calder, B. J., Malthouse, E. C., & Schaedel, U. (2009). An experimental study of the relationship between online engagement and advertising effectiveness. Journal of Interactive Marketing, 23(4), 321–331.
Cha, M., Mislove, A., & Gummadi, K. P. (2009). A measurement-driven analysis of information propagation in the Flickr social network. In Proceedings of the 18th International Conference on World Wide Web (pp. 721–730). ACM.
Edmonds, J., & Karp, R. M. (1972). Theoretical improvements in algorithmic efficiency for network flow problems. Journal of ACM, 19(2), 248–264.
Goldberg, A., & Tarjan, R. (1987). Solving minimum-cost flow problems by successive approximation. In Proceedings of the Nineteenth Annual ACM Symposium on Theory of Computing (pp. 7–18). ACM.
Gruhl, D., Guha, R., Liben-Nowell, D., & Tomkins, A. (2004). Information diffusion through Blogspace. In Proceedings of the International Conference on World Wide Web (pp. 491–501).
Hartline, J., Mirrokni, V., & Sundararajan, M. (2008). Optimal marketing strategies over social networks. Proceedings of the International Conference on World Wide Web (pp. 189–198).
Pletikosa Cvijikj, I., & Michahelles, F. (2013). Online engagement factors on Facebook brand pages. Social Network Analysis and Mining, 3(4), 1869–5450.
Rowe, M., & Alani, H. (2014). Mining and comparing engagement dynamics across multiple social media platforms. Proceedings of the ACM Conference on Web Science (pp. 229–238).
Shen, Y., Dinh, T. N., Zhang, H., & Thai, M. T. (2012). Interest-matching information propagation in multiple online social networks. Proceedings of the ACM International Conference on Information and Knowledge Management (pp. 1824–1828).
Smith, A. N., Fischer, E., & Yongjian, C. (2012). How does brand-related user-generated content differ across YouTube, Facebook, and Twitter? Journal of Interactive Marketing, 26(2), 102–113.
Suh, B., Hong, L., Pirolli, P., & Chi, E. H. (2010). Want to be retweeted? Large scale analytics on factors impacting retweet in twitter network. In IEEE Second International Conference on Social Computing (pp. 177–184).
Szabo, G., & Huberman, B. A. (2010). Predicting the popularity of online content. Communication ACM, 53(8), 80–88.
Vries, L. d., Gensler, S., & Leeflang, P. S. (2012). Popularity of brand posts on brand fan pages: An investigation of the effects of social media marketing. Journal of Interactive Marketing, 26(2), 83–91.
Werthner, H., Alzua-Sorzabal, A., Cantoni, L., Dickinger, A., Gretzel, U., Jannach, D., et al. (2015). Future research issues in IT and tourism. Information Technology and Tourism, 15(1), 1–15.
Acknowledgements
This work has been partially funded by TourPack (http://tourpack.sti2.at), LDCT (http://ldct.sti2.at/) and EuTravel (http://www.eutravelproject.eu/) projects.
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Akbar, Z., Toma, I., Fensel, D. (2016). Optimizing the Publication Flow of Touristic Service Providers on Multiple Social Media Channels. In: Inversini, A., Schegg, R. (eds) Information and Communication Technologies in Tourism 2016. Springer, Cham. https://doi.org/10.1007/978-3-319-28231-2_16
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DOI: https://doi.org/10.1007/978-3-319-28231-2_16
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