Federico Ferro – Thesis. a.a. 2019/2020 LUISS Guido Carli Dipartimento di Impresa e Management Corso di Laurea Magistrale in Marketing Analytics & Metrics Cattedra di Marketing Metrics IMPLEMENTING SENTIMENT ANALYSIS TO ASSESS THE PERCEPTION OF POLARIZING PRODUCT: THE “TESLA CYBERTRUCK” CASE RELATORE CANDIDATO Chiar.mo Prof. Michele Costabile Federico Ferro Matricola N. 704811 CORRELATORE Chiar.mo Prof. Piermario Tedeschi ANNO ACCADEMICO 2019/2020 1 Federico Ferro – Thesis. a.a. 2019/2020 LUISS Guido Carli Dedicata alla mia famiglia 2 Federico Ferro – Thesis. a.a. 2019/2020 LUISS Guido Carli Summary Sharing opinions is an activity that defines social life of humans. People express thoughts to communicate their feelings about events, other people and objects that surround them. These can assume the shape of different emotions, according to how the input impacted and was elaborated by the subject. Thus, an opinion can be seen as a form of elaboration of taste made by a subject towards an object to which he found himself in contact with. Once an opinion is formed, sharing is a subsequent step that allows people to be in contact and thus giving sense to human as a social living being. Thus, expressing an opinion is sometimes a way to express oneself, to tray relating to people in the social fabric. The evolution that sharing have had in modern era is unprecedented, and the main point of this progress is given by the exponential increase of the audience that can elaborate a certain message expressed by one subject. In other terms, nowadays one sender has millions and millions of receivers: if this is multiplied by each subject expressing a thought, the number generated would be just huge. The tool that mostly influenced the change in people’s communication and society in general is Internet, particularly in the form of social media. These are actual platforms that were built for sharing a multitude of information. Everything is this media is focused on allowing each user to share contents, from posts to comments. In some case and for some entities, an opinion can represent a source of value, as it is inserted into a process where its role is giving directions towards the achievement of a certain output. 3 Federico Ferro – Thesis. a.a. 2019/2020 LUISS Guido Carli 4 Federico Ferro – Thesis. a.a. 2019/2020 LUISS Guido Carli Index Figures List ................................................................................................................................................. 6 Tables list ..................................................................................................................................................... 7 Introduction ................................................................................................................................................ 7 1. Elements of Text Mining ............................................................................................................................ 9 1.1. Unstructured Data and Text Mining ............................................................................................................... 9 1.1.1. .......................................................................................................................................... Fields of application and Business relevance ............................................................................................................ 15 1.2. Natural Language Processing ......................................................................................................................... 16 1.2.1. .......................................................................................................................................... Machine Learning Approaches .................................................................................................................................. 18 1.2.2. .......................................................................................................................................... Lexicon-based approach ............................................................................................................................................ 24 1.3. Opinion Mining ................................................................................................................................................ 24 1.3.1. .......................................................................................................................................... Social Media Analysis ............................................................................................................................................... 28 1.4. Literature Review ............................................................................................................................................ 29 2. Object of study: product characteristics ................................................................................................... 37 2.1. The company: Tesla, Inc. ................................................................................................................................ 38 2.1.1. .......................................................................................................................................... Tesla, marketing and social media strategy ............................................................................................................... 47 2.2. The product: Tesla Cybertruck ..................................................................................................................... 55 2.2.1. .......................................................................................................................................... The market-edged nature of Cybertruck .................................................................................................................... 56 2.2.2. .......................................................................................................................................... The Cybertruck unveiling .......................................................................................................................................... 58 2.3. The Electric Pickup sector .............................................................................................................................. 60 3. Application of Sentiment Analysis on product ........................................................................................ 63 3.1. Theoretical Background ................................................................................................................................. 64 3.2. Data Collection ................................................................................................................................................ 65 3.2.1. .......................................................................................................................................... Twitter Data Scraping ................................................................................................................................................ 66 3.3. Text Mining Processing ................................................................................................................................... 68 3.4. Findings ............................................................................................................................................................ 70 5 Federico Ferro – Thesis. a.a. 2019/2020 LUISS Guido Carli 3.4.1. .......................................................................................................................................... Findings of round 1 .................................................................................................................................................... 70 3.4.2. .......................................................................................................................................... Findings of round 2 .................................................................................................................................................... 76 3.4.3. .......................................................................................................................................... Findings of round 3 .................................................................................................................................................... 82 3.4.4. .......................................................................................................................................... Findings of round 4 .................................................................................................................................................... 86 3.5. Discussion and Managerial Implications ...................................................................................................... 90 3.6. Research limits and future perspectives ........................................................................................................ 91 Conclusion ................................................................................................................................................ 92 R Script ...................................................................................................................................................... 93 Bibliography ...........................................................................................................................................