@mastersthesis{development-gsi-mastersthesis-2019,
author = "{\'A}lvarez Fern{\'a}ndez del Vallado, Juan ",
abstract = "This bachelor thesis will detect sarcasm in text. More precisely, the text will be mainly Tweets downloaded from the Twitter social network. The choice of Twitter as the main source of text is due to its great awareness and high popularity among users. Moreover, Twitter offers a vast amount of data which can be freely and very easily downloaded by using simple libraries.

To put it in a nutshell, the data from the Twitter dataset will be analysed using Machine Learning tools as well as other Python-based libraries (i.e. NLP, Pandas). The main objective is to code an algorithm able to learn from the previously downloaded tweets what sarcasm is. Furthermore, once this objective is accomplished, the algorithm should be able to detect sarcasm in tweets.

",
address = "ETSI Telecomunicaci{\'o}n",
institution = "Universidad Polit{\'e}cnica de Madrid",
month = "January",
title = "{D}evelopment of a {S}arcasm {C}lassifier based on {M}achine {L}earning {T}echniques",
type = "TFG",
year = "2019",
}