A Classification of Adjectives for Polarity Lexicons Enhancement

Subjective language detection is one of the most important challenges in Sentiment Analysis. Because of the weight and frequency in opinionated texts, adjectives are considered a key piece in the opinion extraction process. These subjective units are more and more frequently collected in polarity lexicons in which they appear annotated with their prior polarity. However, at the moment, any polarity lexicon takes into account prior polarity variations across domains. This paper proves that a majority of adjectives change their prior polarity value depending on the domain. We propose a distinction between domain dependent and romain independent adjectives. Moreover, our analysis led us to propose a further classification related to subjectivity degree: constant, mixed and highly subjective adjectives. Following this classification, polarity values will be a better support for Sentiment Analysis.

Automatic Extraction of Polar Adjectives for the Creation of Polarity Lexicons

Automatic creation of polarity lexicons is a crucial issue to be solved in order to reduce time andefforts in the first steps of Sentiment Analysis. In this paper we present a methodology based onlinguistic cues that allows us to automatically discover, extract and label subjective adjectivesthat should be collected in a domain-based polarity lexicon. For this purpose, we designed abootstrapping algorithm that, from a small set of seed polar adjectives, is capable to iterativelyidentify, extract and annotate positive and negative adjectives. Additionally, the methodautomatically creates lists of highly subjective elements that change their prior polarity evenwithin the same domain. The algorithm proposed reached a precision of 97.5% for positiveadjectives and 71.4% for negative ones in the semantic orientation identification task.

Mineria d'opinions a Twitter en un entorn multilingüe

L'objectiu d'aquest treball serà fer mineria d'opinions de la xarxa social de microblogging Twitter. En primer lloc, durem a terme una tasca de classificació de sentiments fent servir un lexicó simple. A continuació, emprarem la tècnica de les regles d'associació i, finalment, farem tasques de clustering.

Modelado, extracción y análisis de información del flujo de datos de Twitter

En este artículo se propone el análisis de las interacciones entre usuarios de Twitter, tanto lo que se genera alrededor de un usuario concreto como el análisis de un hashtag dado durante un periodo de tiempo establecido.

Biblio-MetReS: A bibliometric network reconstruction application and server

Background: Reconstruction of genes and/or protein networks from automated analysis of the literature is one of the current targets of text mining in biomedical research. Some user-friendly tools already perform this analysis on precompiled databases of abstracts of scientific papers. Other tools allow expert users to elaborate and analyze the full content of a corpus of scientific documents. However, to our knowledge, no user friendly tool that simultaneously analyzes the latest set of scientific documents available on line and reconstructs the set of genes referenced in those documents is available. Results: This article presents such a tool, Biblio-MetReS, and compares its functioning and results to those of other user-friendly applications (iHOP, STRING) that are widely used. Under similar conditions, Biblio-MetReS creates networks that are comparable to those of other user friendly tools. Furthermore, analysis of full text documents provides more complete reconstructions than those that result from using only the abstract of the document. Conclusions: Literature-based automated network reconstruction is still far from providing complete reconstructions of molecular networks. However, its value as an auxiliary tool is high and it will increase as standards for reporting biological entities and relationships become more widely accepted and enforced. Biblio- MetReS is an application that can be downloaded from http://metres.udl.cat/. It provides an easy to use environment for researchers to reconstruct their networks of interest from an always up to date set of scientific documents.

Aplicación de la técnica de espectrometría de fluorescencia de rayos-X en el estudio de la dispersión de metales en áreas mineras

One critical factor for success in characterizing metals polluting mining environments so as to be able to eliminate them and subsequently recover these areas depends upon a speedy and correct response in the analysis of samples. Rapid, simultaneous, multi-element analysis can be undertaken using X-ray fluorescence spectrometry, a versatile, non-destructive analytical technique commonly employed to identify both major and minor elements in samples related to environmental studies. An additional advantage of this technique is the possibility of conducting the analysis directly on solid samples, which is extremely convenient when dealing with environmental samples that are difficult to dissolve, such as soils, sediments and mining wastes. Moreover, in recent years the development of spectrometers equipped with digital-signal processors combined with enlarged X-ray production, using better designs for excitation-detection, has contributed to an improvement in instrumental sensitivity, thus allowing us to detect important polluting elements such as Cd and Pb at trace levels. In this paper the authors describe, on the basis of their own experience, some interesting applications of XRF spectrometry for the analysis of several types of environmental samples related to the study of the dispersion of metals within mining environments: (A) analysis of mining wastes, soils and sediments; (B) analysis of samples of vegetation used as bioindicators or related to phytoremediation studies; and (C) analysis of water samples related to mining operations

La imagen y el papel de los voluntarios en los Juegos Olímpicos de 1992

Documento que se presentó en la Asignatura Campus de la Universidad Autónoma de Barcelona (UAB) “Olimpismo, Sociedad y Deporte” durante el curso académico 1996/97. El propósito del análisis de este texto es determinar el papel y la imagen de los voluntarios olímpicos antes, durante y después de los Juegos Olímpicos de Barcelona 1992, haciendo hincapié en los aspectos comunicativos, sociales y culturales.

Orientalisme, colonialisme i gènere. ‘El Marroc sensual i fanàtic’ d'Aurora Bertrana

Els autors s’endinsen en aquest article en l’estudi de les relacions entre geografia, orientalisme i colonialisme a Europa al tombant del segle passat, tot introduint la perspectiva de gènere i en el marc d'un interès més general per la història del pensament geogràfic contemporani. Ho fan a partir de l’anàlisi contextualitzada d'un text de l’època que fa referència al cas espanyol i a la seva aventura colonial africana. Es tracta del llibre El Marroc sensual i fanàtic (1936) d’Aurora Bertrana, una versió molt elaborada del discurs de la diferència i una bona il•lustració de la literatura de viatges de dones europees, força excepcional i atípica -això sí- en el context literari català i espanyol de l’època

Destination image of Girona: an online text-mining approach

The main objective of this Master Thesis is to discover more about Girona’s image as a tourism destination from different agents’ perspective and to study its differences on promotion or opinions. In order to meet this objective, three components of Girona’s destination image will be studied: attribute-based component, the holistic component, and the affective component. It is true that a lot of research has been done about tourism destination image, but it is less when we are talking about the destination of Girona. Some studies have already focused on Girona as a tourist destination, but they used a different type of sample and different methodological steps. This study is new among destination studies in the sense that it is based only on textual online data and it follows a methodology based on text-miming. Text-mining is a kind of methodology that allows people extract relevant information from texts. Also, after this information is extracted by this methodology, some statistical multivariate analyses are done with the aim of discovering more about Girona’s tourism image

Analysis and evaluation of techniques for the extraction of classes in the ontology learning process

This paper analyzes and evaluates, in the context of Ontology learning, some techniques to identify and extract candidate terms to classes of a taxonomy. Besides, this work points out some inconsistencies that may be occurring in the preprocessing of text corpus, and proposes techniques to obtain good terms candidate to classes of a taxonomy.

Iron mining in Goa (India) : an interdisciplinary study

En aquest article es presenten breument els diferents capítols d’un treball interdisciplinari per tal d’entendre el context de prohibició de la mineria de ferro a Goa a finals del 2012 i proporcionar la informació necessària per tal d’orientar i gestionar la presa de decisions sobre l’activitat minera en un futur. Els sis primers capítols consisteixen en l’estudi del medi abiòtic, medi biòtic, fluxos de materials, aspectes socials, aspectes econòmics i finalment aspectes polítics. En canvi, en els dos últims capítols s'avaluen i es gestionen els impactes ambientals de la mineria mitjançant, per una banda, una anàlisi DPSIR i, d'altra banda, es proposen tres escenaris per integrar les diferents variables i fomentar la participació en la presa de decisions. S’ha dut a terme una extensa recerca mitjançant la recopilació de dades, entrevistes i visites a les zones d’estudi d’interès per tal d’entendre el conflicte de la mineria a Goa.

Data mining and mall users profile

Marketing scholars have suggested a need for more empirical research on consumer response to malls, in order to have a better understanding of the variables that explain the behavior of the consumers. The segmentation methodology CHAID (Chi-square automatic interaction detection) was used in order to identify the profiles of consumers with regard to their activities at malls, on the basis of socio-demographic variables and behavioral variables (how and with whom they go to the malls). A sample of 790 subjects answered an online questionnaire. The CHAID analysis of the results was used to identify the profiles of consumers with regard to their activities at malls. In the set of variables analyzed the transport used in order to go shopping and the frequency of visits to centers are the main predictors of behavior in malls. The results provide guidelines for the development of effective strategies to attract consumers to malls and retain them there.

A Data mining approach to indirect inference

Consider a model with parameter phi, and an auxiliary model with parameter theta. Let phi be a randomly sampled from a given density over the known parameter space. Monte Carlo methods can be used to draw simulated data and compute the corresponding estimate of theta, say theta_tilde. A large set of tuples (phi, theta_tilde) can be generated in this manner. Nonparametric methods may be use to fit the function E(phi|theta_tilde=a), using these tuples. It is proposed to estimate phi using the fitted E(phi|theta_tilde=theta_hat), where theta_hat is the auxiliary estimate, using the real sample data. This is a consistent and asymptotically normally distributed estimator, under certain assumptions. Monte Carlo results for dynamic panel data and vector autoregressions show that this estimator can have very attractive small sample properties. Confidence intervals can be constructed using the quantiles of the phi for which theta_tilde is close to theta_hat. Such confidence intervals are found to have very accurate coverage.

Using free data mining software and clustering algorithms to find predictors from student qualifications

In this project a research both in finding predictors via clustering techniques and in reviewing the Data Mining free software is achieved. The research is based in a case of study, from where additionally to the KDD free software used by the scientific community; a new free tool for pre-processing the data is presented. The predictors are intended for the e-learning domain as the data from where these predictors have to be inferred are student qualifications from different e-learning environments. Through our case of study not only clustering algorithms are tested but also additional goals are proposed.