The intelligent use of twitter ecosystems by destination management organizations


  • Maria Della Lucia
  • Angelo Presenza
  • Rodolfo Baggio


Destination Management Organization, Destination knowledge and value, Digital business ecosystem, Influential player, Social Media


Purpose of the paper: The paper examines the use of Twitter by destination management organizations in terms of the content communicated and shared and who are the influential players that shape the knowledge conveyed in the ecosystems. It also deepens how the Covid-19 pandemic has impacted these ecosystems.

Methodology: The analysis combines traditional content analysis techniques with modern topic modeling using the specific case of Tourism and Events Queensland (TEQ), the state-level DMO in Queensland, Australia.

Findings: The analyses of the two “Twitter ecosystems” managed by TEQ have shown that not only does each ecosystem have its own knowledge domain and distinguishing characteristics in terms of variety and representativeness of stakeholder category, but it is the influence of the latter that matters in shaping the knowledge domain.

Research limits: The paper deals with a single case study with destination-specific characteristics. It follows that findings cannot necessarily be generalized to other contexts. Longitudinal evaluation studies are also needed to assess the paths taken in terms of stakeholders engaged, themes covered, and tools used by DMOs.

Practical implications: Findings revealed how Twitter is a destination-knowledge-management tool that can be used actively and intentionally by DMOs as intelligent agents to create and manage destination-knowledge in different environments.

Originality of the paper: This paper sheds new light on the intelligent exploitation, by a DMO, of Twitter to enhance destination knowledge management and value creation.


ALBALAWI R., YEAP T.H., BENYOUCEF M. (2020), “Using Topic Modeling Methods for Short-Text Data: A Comparative Analysis”, Frontiers in Artificial Intelligence, vol. 3, n. 42, pp. 1-14.

ANTONIADIS K., ZAFIROPOULOS K., VRANA V. (2015), “Communities of followers in tourism twitter accounts of European countries”, European Journal of Tourism, Hospitality and Recreation, vol. 6 n. 1, pp. 11-26.

BOKUNEWICZ J.F., SHULMAN J. (2017), “Influencer identification in Twitter networks of destination marketing organizations”, Journal of Hospitality and Tourism Technology, vol. 8, n. 2, pp. 205-219.

BORGATTI S.P., EVERETT M.G. (2000), “Models of core/periphery structures”, Social networks, vol. 21, n. 4, pp. 375-395.

CABIDDU F., DE CARLO M., PICCOLI G. (2014). Social media affordances: Enabling customer engagement. Annals of Tourism Research, vol. 48, pp. 175-192.

ĆURLIN T., JAKOVIĆ B., MILOLOŽA I. (2019), “Twitter usage in tourism: Literature review”, Business Systems Research: International Journal of the Society for Advancing Innovation and Research in Economy, vol. 10, n. 1, pp. 102-119.

D’HEER E., VERDEGEM P. (2015), “What social media data mean for audience studies: A multidimensional investigation of Twitter use during a current affairs TV programme”, Information, Communication & Society, vol. 18, n. 2, n. 221-234.

DE BRUIJN J. A., DE MOEL H., JONGMAN B., WAGEMAKER J., AERTS J.C. (2018), “TAGGS: Grouping tweets to improve global geoparsing for disaster response”, Journal of Geovisualization and Spatial Analysis, vol. 2, n. 2, pp. 1-14.

EISENHARDT K.M. (1989), “Building theories from case study research”, Academy of Management Review, vol. 14, n. 4, pp. 532-550.

FELLMAN J. (2012), “Estimation of Gini coefficients using Lorenz curves”, Journal of Statistical and Econometric Methods, vol. 1, n. 2, pp. 31-38.

GALLAGHER R.J., YOUNG J.G., WELLES B.F. (2021), “A clarified typology of core-periphery structure in networks”, Science advances, vol. 7, n. 12, 1-11.

GIBBS C., DANCS A. (2013), “Understanding destination management organizations use of Twitter: A content analysis of tweets”, in Proceedings of the Travel and Tourism Research Association Conference, Ottawa.

HASAN S., UKKUSURI S.V. (2015), “Location contexts of user check-ins to model urban geo life-style patterns”, PloS one, vol. 10, n. 5, pp. 1-19.

HAYS S., PAGE S., BUHALIS D. (2013), “Social media as a destination marketing tool: Its use by national tourism organisations”, Current Issues in Tourism, vol. 16, n. 3, pp. 211-239.

HSIEH H.F., SHANNON S.E. (2005), “Three approaches to qualitative content analysis”, Qualitative Health Research, vol. 15, n. 9, pp. 1277-1288.

ISOAHO K., GRITSENKO D., MÄKELÄ E. (2021), “Topic modelling and text analysis for qualitative policy research”, Policy Studies Journal, vol. 49, n. 1, pp. 300-324.

JABREEL M., MORENO A., HUERTAS A. (2016), “Semantic comparison of the emotional values communicated by destinations and tourists on social media”, Journal of Destination Marketing and Management, vol. 6, n. 3, pp. 170-183.

JIN X., CHENG M. (2020), “Communicating mega events on Twitter: Implications for destination marketing”, Journal of Travel & Tourism Marketing, vol. 37, n. 6, pp. 739-755.

KRONENBERG K., FUCHS M. (2022), “The socio-economic impact of regional tourism: an occupation-based modelling perspective from Sweden”, Journal of Sustainable Tourism, vol. 30, n. 12, pp. 2785-2805.

KUMAR P., MISHRA J.M., RAO Y.V. (2022), “Analysing tourism destination promotion through Facebook by Destination Marketing Organizations of India”, Current Issues in Tourism, vol. 25, n. 9, pp. 1416-1431.

MIAH S.J., VU H.Q., GAMMACK J., MCGRATH M. (2017), “A big data analytics method for tourist behaviour analysis”, Information & Management, vol. 54, n. 6, pp. 771-785.

MUNAR A.M. (2012), “Social media strategies and destination management”, Scandinavian Journal of Hospitality and Tourism, vol. 12, pp. 101-120.

NOOR S., GUO Y., SHAH S.H.H., HALEPOTO H. (2021), “Thematic Analysis of Twitter as a Platform for Knowledge Management, in Proceedings International Conference on Knowledge Science, Engineering and Management (pp. 610-618), Springer, Cham.

PARESCHI L., MOLLONA E. (2020), “Comparing qualitative content analysis and semi-automatic text analysis through Topic Modelling: the discourse on Italian steel privatizations”, in Proceedings EURAM 2020 conference, Dublin.

RACHERLA P., HU C., HYUN M.Y. (2008), “Exploring the role of innovative technologies in building a knowledge-based destination”, Current Issues in Tourism, vol. 11, n. 5, pp. 407-428.

ŘEHŮŘEK R., SOJKA P. (2010), “Software framework for topic modelling with large corpora, LREC 2010 Workshop on New Challenges for NLP Frameworks, 19–21 May, Valletta, Malta, pp. 45¬50.

ROESSLEIN J. (2020), “Tweepy. Twitter for Python”, in

SENYO P.K., LIU K., EFFAH J. (2019), “Digital business ecosystem: Literature review and a framework for future research”, International Journal of Information Management, vol. 47, pp. 52-64.

SEVIN E. (2013), “Places going viral: Twitter usage patterns in destination marketing and place branding”, Journal of Place Management and Development, vol. 6, n. 3, pp. 227-239.

SHEEHAN L., VARGAS-SÁNCHEZ A., PRESENZA A., ABBATE T. (2016), “The use of intelligence in tourism destination management: An emerging role for DMOs”, International Journal of Tourism Research, vol. 18, n. 6, pp. 549-557.

SIGALA M. (2018), “New technologies in tourism: From multi-disciplinary to anti-disciplinary advances and trajectories”, Tourism Management Perspectives, vol. 25, pp. 151-155.

SOCIALBAKERS (2015), Social bakers analytics. User guide, in

SWANI K., BROWN B.P., MILNE G.R. (2014), Should tweets differ for B2B and B2C? An analysis of Fortune 500companies’ Twitter communications, Industrial Marketing Management, vol. 43, n. 5, pp. 873-881.

TRUNFIO M., DELLA LUCIA M. (2019), “Engaging destination stakeholders in the digital era: The best practice of Italian regional DMOs”, Journal of Hospitality & Tourism Research, vol. 43, n. 3, pp. 349-373.

VOLGGER M., PECHLANER H. (2014), “Requirements for destination management organizations in destination governance: Understanding DMO success”, Tourism Management, vol. 41, pp. 64-75.

ZHANG Y., WILDEMUTH B.M. (2005), “Qualitative analysis of Content”, Human Brain Mapping, vol. 30, n. 7, pp. 2197-2209.