The huge amount of textual information that exists on social networks added by users through comments, has aroused a great interest in companies and research groups, which seek to use this information to identify trends and acceptance levels of brands, products, and services. A technique to know the level of acceptance or rejection of a particular topic, in an automated way, is the Sentiment Analysis. Some informatics tools incorporate this technique, however, there are few contributions to texts in Spanish. It is because of the difficulty of identifying different contexts, dialects, complex grammatical structures, and semantic language variances in each region. This article presents a web tool for the analysis of sentiments in texts written in Spanish that include Ecuadorian dialect or idioms. The tool was developed in R-Shiny with an approach lexicon-based. The tool allows the customization of the lexicons based on context and facilitates the automatic download of tweets according to search criteria such as the place, dates, and topic. To evaluate the effectiveness of the application, their result was compared with two commercial tools (Azure Text Analytics and IBM Watson NLU) and a manual score carried out by a group of people. The tests include the analysis of three corpora created from tweets. The results show the effectiveness of the tool to identify the sentiment polarity, especially in texts that include dialects, colloquial words, and negative expressions.
|Title of host publication||Conference Proceeding - ACAI 2020|
|Subtitle of host publication||2020 3rd International Conference on Algorithms, Computing and Artificial Intelligence|
|Publisher||Association for Computing Machinery|
|State||Published - 24 Dec 2020|
|Event||3rd International Conference on Algorithms, Computing and Artificial Intelligence, ACAI 2020 - Sanya, China|
Duration: 24 Dec 2020 → 26 Dec 2020
|Name||ACM International Conference Proceeding Series|
|Conference||3rd International Conference on Algorithms, Computing and Artificial Intelligence, ACAI 2020|
|Period||24/12/20 → 26/12/20|
Bibliographical noteFunding Information:
Supported by the suite of tools provided by the R platform, this work shows the development of a free access web tool, called Sentimental Analysis on Ecuadorian Tweets (SAET), which aims to incorporate idioms and Spanish words in the Ecuadorian context. The tool performs a personalized sentiment analysis of the text, calculates the polarity of each tweet, and creates interactive visualizations of the results.
© 2020 ACM.
- Azure Text Analytics
- IBM Watson NLU