A systemic and cybernetic perspective on causality, big data and social networks in tourism

Purpose The purpose of this paper is to propose a mathematical model to determine invariant sets, set covering, orbits and, in particular, attractors in the set of tourism variables. Analysis was carried out based on an algorithm and applying an interpretation of chaos theory developed in the context of General Systems Theory and Big Data. Design/methodology/approach Tourism is one of the most digitalized sectors of the economy, and social networks are an important source of data for information gathering.

Overview of TASS 2018: Opinions, Health and Emotions Resumen de TASS 2018: Opiniones, Salud y Emociones

This is an overview of the Workshop on Semantic Analysis at the SEPLN congress held in Sevilla, Spain, in September 2018. This forum proposes to participants four different semantic tasks on texts written in Spanish. Task 1 focuses on polarity classification; Task 2 encourages the development of aspect-based polarity classification systems; Task 3 provides a scenario for discovering knowledge from eHealth documents; finally, Task 4 is about automatic classification of news articles according to safety. The former two tasks are novel in this TASS’s edition.

A Bootstrapping Technique to Annotate Emotional Corpora Automatically

In computational linguistics, the increasing interest of the detection of emotional and personality profiles has given birth to the creation of resources that allow the detection of these profiles. This is due to the large number of applications that the detection of emotion states can have, such as in e-learning environment or suicide prevention. The development of resources for emotional profiles can help to improve emotion detection techniques such as supervised machine learning, where the development of annotated corpora is crucial.

Exploiting a Bootstrapping Approach for Automatic Annotation of Emotions in Texts

The objective of this research is to develop a technique to automatically annotate emotional corpora. The complexity of automatic annotation of emotional corpora still presents numerous challenges and thus there is a need to develop a technique that allow us to tackle the annotation task. The relevance of this research is demonstrated by the fact that people's emotions and the patterns of these emotions provide a great value for business, individuals, society or politics. Hence, the creation of a robust emotion detection system becomes crucial.

DrugSemantics: A corpus for Named Entity Recognition in Spanish Summaries of Product Characteristics

For the healthcare sector, it is critical to exploit the vast amount of textual health-related information. Nevertheless, healthcare providers have difficulties to benefit from such quantity of data during pharmacotherapeutic care. The problem is that such information is stored in different sources and their consultation time is limited.


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