2026-06-07T07:12:59Zhttps://riuma.uma.es/rest/oai/request

oai:riuma.uma.es:10630/294752026-02-03T11:08:07Zcom_10630_2254col_10630_37953

00925njm 22002777a 4500 dc García Gámez, María author Moreno-Ortiz, Antonio Jesús author 2022-06 Sentiment analysis is a natural language processing task that has received increased attention in the last decade due to the vast amount of opinionated data on social media platforms such as Twitter. Although the methodologies employed have grown in number and sophistication, analysing irony and sarcasm still poses a severe problem. From the linguistic perspective, sarcasm has been studied in discourse analysis from several perspectives, but little attention has been given to specific metrics that measure its relevance. In this paper we describe the creation of a manually-annotated dataset where detailed text markers are included. This dataset is a sample from a larger corpus of tweets (n= 76,764) on two highly controversial films: Cats and Star Wars: The Rise of Skywalker. We took two different samples for each film, one before and one after their release, to compare reception and presence of sarcasm. We then used a sentiment analysis tool to measure the impact of sarcasm in polarity detection and then manually classified the mechanisms of sarcasm generation. The resulting corpus will be useful for machine learning approaches to sarcasm detection as well as discourse analysis studies on irony and sarcasm. Moreno-Ortiz, A. J., & García-Gámez, M. (2022). Corpus Annotation and Analysis of Sarcasm in Twitter: #CatsMovie vs. #TheRiseOfSkywalker. Atlantis. Journal of the Spanish Association for Anglo-American Studies, 186–207. https://doi.org/10.28914/Atlantis-2022-44.1.11 https://hdl.handle.net/10630/29475 10.28914/Atlantis-2022-44.1.11 Redes sociales en internet Ironía Corpus annotation and analysis of sarcasm on Twitter: #CatsMovie vs. #TheRiseOfSkywalker