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Found 12 papers, 4 papers with code
Are metrics measuring what they should? An evaluation of image captioning task metrics
Looking to measure how well or not the set of current and more recent metrics are doing, in this article, we present an evaluation of several kinds of Image Captioning metrics and a comparison between them using the well-known MS COCO dataset.
Video Captioning: a comparative review of where we are and which could be the route
As a result, the most-used datasets and metrics are identified.
Regionalized models for Spanish language variations based on Twitter
Spanish is one of the most spoken languages in the globe, but not necessarily Spanish is written and spoken in the same way in different countries.
A Case Study of Spanish Text Transformations for Twitter Sentiment Analysis
Sentiment analysis is a text mining task that determines the polarity of a given text, i. e., its positiveness or negativeness.
Infotec + CentroGEO at SemEval-2020 Task 8: Deep Learning and Text Categorization approach for Memes classification
We obtained results analyzing the text and images separately, and also in combination.
INGEOTEC at SemEval-2020 Task 12: Multilingual Classification of Offensive Text
This paper describes our participation in OffensEval challenges for English, Arabic, Danish, Turkish, and Greek languages.
A Python Library for Exploratory Data Analysis on Twitter Data based on Tokens and Aggregated Origin-Destination Information
Twitter is perhaps the social media more amenable for research.
EvoMSA: A Multilingual Evolutionary Approach for Sentiment Analysis
Furthermore, we performed an analysis of EvoMSA's components to measure their contribution to the performance; the idea is to facilitate a practitioner or newcomer to implement a competitive SA classifier.
INGEOTEC at SemEval-2018 Task 1: EvoMSA and μTC for Sentiment Analysis
This paper describes our participation in Affective Tweets task for emotional intensity and sentiment intensity subtasks for English, Spanish, and Arabic languages.
INGEOTEC at SemEval 2017 Task 4: A B4MSA Ensemble based on Genetic Programming for Twitter Sentiment Analysis
This paper describes the system used in SemEval-2017 Task 4 (Subtask A): Message Polarity Classification for both English and Arabic languages.
An Automated Text Categorization Framework based on Hyperparameter Optimization
The compared datasets include several problems like topic and polarity classification, spam detection, user profiling and authorship attribution.
A Simple Approach to Multilingual Polarity Classification in Twitter
Recently, sentiment analysis has received a lot of attention due to the interest in mining opinions of social media users.
