Lingmotif: A Userfocused Sentiment Analysis Tool espanolEn este articulo se describe Lingmotif, una aplicacion de Analisis de Sentimiento multiplataforma, con interfaz grafica de usuario amigable, motivada linguisticamente y basada en lexico. Lingmotif efectua Analisis de Sentimiento sobre cualquier tipo de texto, independientemente de su tamano o tema. El analisis se basa en la identificacion en el texto de palabras y frases con carga afectiva, contenidas en los diccionarios de la aplicacion, y aplica reglas de contexto para dar cabida a modificadores del sentimiento. Ofrece representaciones graficas faciles de interpretar de los datos cuantitativos, asi como un analisis detallado del texto. Lingmotif tambien puede utilizar lexicos del usuario a modo de plugins, de tal modo que es posible analizar de forma efectiva la expresion del sentimiento en dominios especificos. La version 1.0 de Lingmotif esta preparada para trabajar con textos en espanol e ingles. De este modo, se conforma como una herramienta de proposito general en el ambito del Analisis de Sentimiento para el analisis del discurso, retorica, psicologia, marketing, las industrias de la lengua y otras. EnglishIn this paper, we describe Lingmotif, a lexiconbased, linguisticallymotivated, userfriendly, GUIenabled, multiplatform, Sentiment Analysis desktop application. Lingmotif can perform SA on any type of input texts, regardless of their length and topic. The analysis is based on the identification of sentimentladen words and phrases contained in the applicationu0027s rich core lexicons, and employs context rules to account for sentiment shifters. It offers easytointerpret visual representations of quantitative data, as well as a detailed, qualitative analysis of the text in terms of its sentiment. Lingmotif can also take userprovided plugin lexicons in order to account for domainspecific sentiment expression. As of version 1.0, Lingmotif analyzes English and Spanish texts. Lingmotif thus aims to become a generalpurpose Sentiment Analysis tool for discourse analysis, rhetoric, psychology, marketing, the language industries, and others.

VISTX: Experimenting with Interactive Stance and Sentiment Visualisation Usergenerated content online continues to grow rapidly, and with this it becomes more challenging to evaluate the general consensus on a trending topic. Even greater challenges are faced if one wishes to compare opinions across multiple topics, as it can be difficult to make comparisons and reach conclusions with large amounts of data in an intuitive manner. VISTX explores innovative methods of visualising opinion in terms of stance and sentiment using Twitter data from the SemEval2016 Stance Dataset and presents three types of interactive visualisations. We discuss the method of testing the visualisations for effectiveness with a small group of users, where time taken and the number of incorrect interpretations were measured for each user. We discuss the results, which indicate that the xe2x80x98circlepackingxe2x80x99 visualisation type may lead to quicker interpretations for five or more topics. Finally, we discuss the work needed to further solidify these initial findings.