Enhancing Decision Making Capacity in Tourism Domain Using Social Media Analytics
Autor: | Tharindu Bandaragoda, Supun Abeysinghe, Prabod Rathnayaka, Chamod Samarajeewa, Damminda Alahakoon, Malaka J. Walpola, Rashmika Nawaratne, Isura Manchanayake |
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Rok vydání: | 2018 |
Předmět: |
Social and Information Networks (cs.SI)
FOS: Computer and information sciences Computer Science - Machine Learning Computer science 020207 software engineering Computer Science - Social and Information Networks 02 engineering and technology 010501 environmental sciences Business value 01 natural sciences Data science Popularity Social media analytics Visualization Domain (software engineering) Task (project management) Computer Science - Information Retrieval Machine Learning (cs.LG) 0202 electrical engineering electronic engineering information engineering Social media Tourism Information Retrieval (cs.IR) 0105 earth and related environmental sciences |
DOI: | 10.48550/arxiv.1812.08330 |
Popis: | Social media has gained an immense popularity over the last decade. People tend to express opinions about their daily encounters on social media freely. These daily encounters include the places they traveled, hotels or restaurants they have tried and aspects related to tourism in general. Since people usually express their true experiences on social media, the expressed opinions contain valuable information that can be used to generate business value and aid in decision-making processes. Due to the large volume of data, it is not a feasible task to manually go through each and every item and extract the information. Hence, we propose a social media analytics platform which has the capability to identify discussion pathways and aspects with their corresponding sentiment and deeper emotions using machine learning techniques and a visualization tool which shows the extracted insights in a comprehensible and concise manner. Identified topic pathways and aspects will give a decision maker some insight into what are the most discussed topics about the entity whereas associated sentiments and emotions will help to identify the feedback. Comment: To Appear in Proceedings of International Conference on Advances in ICT for Emerging Regions, Colombo, LK |
Databáze: | OpenAIRE |
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