Tourists, Data & Social Media: How the Use of Big Social Data Analytics Can Guide the Development of Successful Social Media Strategies in Destination Marketing

Thomas Kersig

Student thesis: Master thesis

Abstract

This study investigates how the use of big social data analytics can help destination management organizations (DMO’s) develop successful Social Media (SoMe) marketing strategies based on an analysis of the Facebook page activity of Copenhagen’s official tourism site, “VisitCopenhagen”. Following a manual categorization of 1.397 posts published between 01.01.2014 and 02.12.2016 by means of content analysis, big social data analytics techniques were used to gain insights about the performance of the disseminated content. Descriptive- and visual analytics were applied to determine user engagement on the one hand, while text classification by means of LinearSVC was applied to detect sentiment on the other hand. Moreover, topic modeling using Latent Dirichlet Allocation (LDA) was performed to identify trending topics amongst users. The findings demonstrate the applicability of these techniques to inform DMO’s Social Media marketing strategies by identifying performance trends and consequent areas for improvement. While adding to the relatively scant stream of research on DMO’s use of Social Media, this paper advances existing efforts of analyzing SoMe marketing performance by complementing previously used methods based on simple descriptive statistics with advanced machine learning techniques

EducationsMSc in Business Administration and E-business, (Graduate Programme) Final Thesis
LanguageEnglish
Publication date2019
Number of pages73
SupervisorsAbid Hussain