Understanding Public Opinion towards New Sharing Economy Business Model Using Content Analysis Andry Alamsyah School of Economic and Business Telkom University Bandung, Indonesia andrya@telkomuniversity.ac.id Wachda Yuniar Rochmah School of Economic and Business Telkom University Bandung, Indonesia wachdayuniar@gmail.com Ditya Dwi Adhi Nugroho School of Economic and Business Telkom University Bandung, Indonesia dityaadhi@outlook.com Abstract—Hospitality, as one of the sectors in the tourism industry, continues to show positive trend every year based on its revenues. In order to understand public opinion, the legacy method such as interview, questionnaire, and other time- consuming method is still widely used in this sector. However, this method is less efficient compared to data analytics methodology using available data from online source, such as social media Therefore, we need to conduct a research to see a better method in order to understand the public opinion in hospitality sector. There are many methodologies to support content analysis based on unstructured data to understand public opinion. In this research, we use content analysis methodology which consists of Sentiment Analysis, Topic Modeling, and Text Network Analysis to process 483413 obtained tweets from January 7 th until March 28 th , 2017. The twitter data is gained using Python and R language. The whole process of the research consists of data collection, data preprocessing, and interpreting the results. We use Rstudio, Jupyter Notebook and Gephi softwares during the process. As a case study in the hospitality sector, we use Airbnb as one of the sharing economy business models that allows other people to share their space and begins to be widely used by travelers around the world. Our objective is to understand public opinion towards Airbnb as online-based sharing economy business model which becomes a disruptive innovation for tourism industry. As the result, we are able to apply the combination of content analysis methods to give a good understanding towards the public opinion. Text Network Analysis gives us the ability to summarise large-scale conversation in very fast and real-time fashion. It provides the knowledge by associate most frequent words used in social conversations. Sentiment Analysis shows the feelings and emotion from people about certain topics. Topic Modelling is able to capture popular topics, thus gives comprehensive understanding on how people react towards a new business model Keywords—sharing economy, content analysis, sentiment analysis, topic modeling, text network analysis I. INTRODUCTION Sharing economy allows society to arrange their everyday task into new ways of life such as; drive people around, or share extra rooms. Moreover, another type of sharing economy startup also enables its consumer to share their ideas or information, such as Facebook, Twitter, and other social media. [1]. Sharing economy business gives them more power to people want to utilize their assets. Thus, it provides more efficient way than traditional service. In addition, it also affects the stability of established companies due to its low price. However, they have to face the challenge such as the regulation which is different in each country. As the case study, Airbnb is an online-base sharing economy that provides various services, including rental. It empowers many people around the world because people are able to monetize their properties Travelers can have access to stay in various kind of places, from a villa to a castle. All of them are brought together in their website and app. The company, established in 2008, has conquered the global market in many countries and becomes one of the big rental places. They provide access to more than 5 million places to stay, spread in 191 countries around the world [2]. Following the democratization sharing information related to a product or service in an online social network, customers share their opinions on social media, including Airbnb customers. Thus, in this research we investigate public opinion towards Airbnb as a new sharing economy business model using pattern exploration based data analytics instead of traditional approaches such as a questionnaire or interview which doesn’t give the comprehensive view of the public opinion. We apply several content analysis methodology which consist of Text Network Analysis, Sentiment Analysis, and Topic Modeling to understand comprehensively customer's perception towards Airbnb as a new sharing economy business. Previous researches have applied these methods in order to understand customer’s level of satisfaction to the company or competitors [3] and in a large scale data [4]. As the final result of this research, we are able to identify the topics from the positive and negative opinions and see the relation of the words which are being talked by people. II. LITERATURE REVIEW A. Sharing economy The Sharing economy is a new concept to share the human and physical resource, including the goods and services of different people and organizations. The goal is to allow the sharing and collaboration in all social economic aspects of life, such as collaborative consumption, shared ownership, renting, borrowing, lending, etc. [5]. A collaborative consumption has been expected to lessen problems such as poverty, hyper consumption, or even pollution [6]. Alongside with its advantage, trust has become the main reason of people to engage with sharing economy and distinguished itself from existing rental service [7]. B. Content Analysis Content analysis is a set of methodologies to analyze written, verbal, or visual communication message [8]. It is