English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Users express their feelings about an entity of a specific topic in a free way using short texts on social networks. Sentiment analysis, also known as opinion mining, focuses on examining these texts to determine their polarity. This article presents an approach to the mining of opinions based on topics from Twitter texts in Spanish. The main objective is to decide the polarity of a text, determining if the content has positive, negative or neutral implications in the reputation of entities for a topic. In this paper a supervised approach is used for the classification of texts using the word bag model for the representation of characteristics. The experimentation shows promising results, providing a resource for the analysis of texts in Spanish.

Minería de opiniones centrada en tópicos usando textos cortos en español