Reaction Prediction: The Case of Tweets from Luxury Fashion Brands

Social media platforms represent an essential tool for both consumers and marketers. Meanwhile, luxury fashion brands play a key role in fashion, one of the most important industries of the world economy. Despite assumptions to the contrary, social media platforms and luxury fashion brands do mix...

Descripción completa

Detalles Bibliográficos
Autor principal: Calviello Crusella, Chiara
Otros Autores: Cisco, Santiago
Formato: Tesis de maestría acceptedVersion
Lenguaje:Inglés
Publicado: Universidad Torcuato Di Tella 2023
Materias:
Redes Sociales (en línea)
Social Media Patforms
Comportamiento del Consumidor
Consumer behavior
Twitter
Luxury Fashion brands
Tweet reaction overall score (TROS)
Acceso en línea:https://repositorio.utdt.edu/handle/20.500.13098/12026
Aporte de:
Repositorio Digital Universidad Torcuato Di Tella de Universidad Torcuato Di Tella
id I57-R163-20.500.13098-12026
record_format dspace
spelling I57-R163-20.500.13098-120262023-11-14T07:28:18Z Reaction Prediction: The Case of Tweets from Luxury Fashion Brands Calviello Crusella, Chiara Cisco, Santiago Redes Sociales (en línea) Social Media Patforms Comportamiento del Consumidor Consumer behavior Twitter Luxury Fashion brands Tweet reaction overall score (TROS) Social media platforms represent an essential tool for both consumers and marketers. Meanwhile, luxury fashion brands play a key role in fashion, one of the most important industries of the world economy. Despite assumptions to the contrary, social media platforms and luxury fashion brands do mix, especially in the recent time. Consequently, it is worth asking whether it is possible to predict the reaction a post will generate in the audience of luxury fashion brands. This new question is the one this thesis intends to answer. To do so, the concept of reaction is defined through a novel composite index that is created and named Tweet reaction overall score (TROS), which is one of the solid and relevant contributions this thesis makes. Then, several predictive models are implemented, based on a wide range of different learning algorithms. The results show that it is indeed possible to predict the TROS that a post on Twitter will obtain in the audience of luxury fashion brands the day it is posted. 2023-09-19T19:44:36Z 2023-09-19T19:44:36Z 2023 info:eu-repo/semantics/masterThesis info:ar-repo/semantics/tesis de maestría info:eu-repo/semantics/acceptedVersion https://repositorio.utdt.edu/handle/20.500.13098/12026 eng info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by-sa/2.5/ar/ 119 p. application/pdf application/pdf Universidad Torcuato Di Tella
institution Universidad Torcuato Di Tella
institution_str I-57
repository_str R-163
collection Repositorio Digital Universidad Torcuato Di Tella
language Inglés
orig_language_str_mv eng
topic Redes Sociales (en línea)
Social Media Patforms
Comportamiento del Consumidor
Consumer behavior
Twitter
Luxury Fashion brands
Tweet reaction overall score (TROS)
spellingShingle Redes Sociales (en línea)
Social Media Patforms
Comportamiento del Consumidor
Consumer behavior
Twitter
Luxury Fashion brands
Tweet reaction overall score (TROS)
Calviello Crusella, Chiara
Reaction Prediction: The Case of Tweets from Luxury Fashion Brands
topic_facet Redes Sociales (en línea)
Social Media Patforms
Comportamiento del Consumidor
Consumer behavior
Twitter
Luxury Fashion brands
Tweet reaction overall score (TROS)
description Social media platforms represent an essential tool for both consumers and marketers. Meanwhile, luxury fashion brands play a key role in fashion, one of the most important industries of the world economy. Despite assumptions to the contrary, social media platforms and luxury fashion brands do mix, especially in the recent time. Consequently, it is worth asking whether it is possible to predict the reaction a post will generate in the audience of luxury fashion brands. This new question is the one this thesis intends to answer. To do so, the concept of reaction is defined through a novel composite index that is created and named Tweet reaction overall score (TROS), which is one of the solid and relevant contributions this thesis makes. Then, several predictive models are implemented, based on a wide range of different learning algorithms. The results show that it is indeed possible to predict the TROS that a post on Twitter will obtain in the audience of luxury fashion brands the day it is posted.
author2 Cisco, Santiago
author_facet Cisco, Santiago
Calviello Crusella, Chiara
format Tesis de maestría
Tesis de maestría
acceptedVersion
author Calviello Crusella, Chiara
author_sort Calviello Crusella, Chiara
title Reaction Prediction: The Case of Tweets from Luxury Fashion Brands
title_short Reaction Prediction: The Case of Tweets from Luxury Fashion Brands
title_full Reaction Prediction: The Case of Tweets from Luxury Fashion Brands
title_fullStr Reaction Prediction: The Case of Tweets from Luxury Fashion Brands
title_full_unstemmed Reaction Prediction: The Case of Tweets from Luxury Fashion Brands
title_sort reaction prediction: the case of tweets from luxury fashion brands
publisher Universidad Torcuato Di Tella
publishDate 2023
url https://repositorio.utdt.edu/handle/20.500.13098/12026
work_keys_str_mv AT calviellocrusellachiara reactionpredictionthecaseoftweetsfromluxuryfashionbrands
_version_ 1808040606093541376

Ejemplares similares