Socialising Around Media (SAM): Dynamic Social and Media Content Syndication for Second Screen

Today's generation of Internet devices has changed how users are interacting with media, from passive and unidirectional users to proactive and interactive. Users can use these devices to comment or rate a TV show and search for related information regarding characters, facts or personalities. This phenomenon is known as second screen. This paper describes SAM, an EU-funded research project that focuses on developing an advanced digital media delivery platform based on second screen interaction and content syndication within a social media context, providing open and standardised ways of characterising, discovering and syndicating digital assets. This work provides an overview of the project and its main objectives, focusing on the NLP challenges to be faced and the technologies developed so far.

ElectionMap: una representación geolocalizada de intenciones de voto hacia partidos políticos sobre la base de comentarios de usuarios de Twitter

ElectionMap es una aplicación web que realiza un seguimiento a los comentarios publicados en Twitter en relación a entidades que refieren a partidos políticos. Las opiniones de los usuarios sobre estas entidades son clasificadas según su valoración y posteriormente representadas en un mapa geográfico para conocer la aceptación social sobre agrupaciones políticas en las distintas regiones de la geografía española.

Social Rankings: análisis visual de sentimientos en redes sociales

Social Rankings es una aplicación web que realiza un seguimiento en tiempo real de entidades en las redes sociales. Detecta y analiza las opiniones sobre estas entidades utilizando técnicas de análisis de sentimientos para generar un informe visual de su valoración y su evolución en el tiempo.

A review on political analysis and social media

En los países democráticos, conocer la intención de voto de los ciudadanos y las valoraciones de los principales partidos y líderes políticos es de gran interés tanto para los propios partidos como para los medios de comunicación y el público en general. Para ello se han utilizado tradicionalmente costosas encuestas personales. El auge de las redes sociales, principalmente Twitter, permite pensar en ellas como una alternativa barata a las encuestas. En este trabajo, revisamos la bibliografía científica más relevante en este ámbito, poniendo especial énfasis en el caso español.

An overview of the Applications of Natural Language to Information Systems

This introduction provides an overview of the state-of-the-art technology in Applications of Natural Language to Information Systems. Specifically, we analyze the need for such technologies to successfully address the new challenges of modern information systems, in which the exploitation of the Web as a main data source on business systems becomes a key requirement. It will also discuss the reasons why Human Language Technologies themselves have shifted their focus onto new areas of interest very directly linked to the development of technology for the treatment and understanding of Web 2.0. These new technologies are expected to be future interfaces for the new information systems to come. Moreover, we will review current topics of interest to this research community, and will present the selection of manuscripts that have been chosen by the program committee of the NLDB 2011 conference as representative cornerstone research works, especially highlighting their contribution to the advancement of such technologies.

Applying semantic knowledge to the automatic processing of temporal expressions and events in natural language

This paper addresses the problem of the automatic recognition and classification of temporal expressions and events in human language. Efficacy in these tasks is crucial if the broader task of temporal information processing is to be successfully performed. We analyze whether the application of semantic knowledge to these tasks improves the performance of current approaches. We therefore present and evaluate a data-driven approach as part of a system: TIPSem. Our approach uses lexical semantics and semantic roles as additional information to extend classical approaches which are principally based on morphosyntax. The results obtained for English show that semantic knowledge aids in temporal expression and event recognition, achieving an error reduction of 59% and 21%, while in classification the contribution is limited. From the analysis of the results it may be concluded that the application of semantic knowledge leads to more general models and aids in the recognition of temporal entities that are ambiguous at shallower language analysis levels. We also discovered that lexical semantics and semantic roles have complementary advantages, and that it is useful to combine them. Finally, we carried out the same analysis for Spanish. The results obtained show comparable advantages. This supports the hypothesis that applying the proposed semantic knowledge may be useful for different languages.

How to make a natural language interface to query databases accessible to everyone: An example

Natural Language Interfaces to Query Databases (NLIDBs) have been an active research field since the 1960s. However, they have not been widely adopted. This article explores some of the biggest challenges and approaches for building NLIDBs and proposes techniques to reduce implementation and adoption costs. The article describes {AskMe*}, a new system that leverages some of these approaches and adds an innovative feature: query-authoring services, which lower the entry barrier for end users. Advantages of these approaches are proven with experimentation. Results confirm that, even when {AskMe*} is automatically reconfigurable against multiple domains, its accuracy is comparable to domain-specific NLIDBs.

An approach based on Logic Forms and WordNet relationships to Textual Entailment performance

This paper outlines the approach adopted by the PLSI research group at University of Alicante in the PASCAL-2006 second Recognising Textual Entailment challenge. Our system is composed of several components. On the one hand, the first component performs the derivation of the logic forms of the text/hypothesis pairs and, on the other hand, the second component provides us with a similarity score given by the semantic relations between the derived logic forms. In order to obtain this score we apply several measures of similitude and relatedness based on the structure and content of WordNet.

The OpAL System at NTCIR 8 MOAT

The present is marked by the availability of large volumes of heterogeneous data, whose management is extremely complex. While the treatment of factual data has been widely studied, the processing of subjective information still poses important challenges. This is especially true in tasks that combine Opinion Analysis with other challenges, such as the ones related to Question Answering. In this paper, we describe the different approaches we employed in the NTCIR 8 MOAT monolingual English (opinionatedness, relevance, answerness and polarity) and cross-lingual English-Chinese tasks, implemented in our OpAL system. The results obtained when using different settings of the system, as well as the error analysis performed after the competition, offered us some clear insights on the best combination of techniques, that balance between precision and recall. Contrary to our initial intuitions, we have also seen that the inclusion of specialized Natural Language Processing tools dealing with Temporality or Anaphora Resolution lowers the system performance, while the use of topic detection techniques using faceted search with Wikipedia and Latent Semantic Analysis leads to satisfactory system performance, both for the monolingual setting, as well as in a multilingual one.

Recognizing and tagging temporal expressions in Spanish

This paper shows a system about the recognition of temporal expressions in Spanish and the resolution of their temporal reference. For the identification and recognition of temporal expressions we have based on a temporal expression grammar and for the resolution on an inference engine, where we have the information necessary to do the date operation based on the recognized expressions. For further information treatment, the output is proposed by means of XML tags in order to add standard information of the resolution obtained. Different kinds of annotation of temporal expressions are explained in another articles [WILSON2001][KATZ2001]. In the evaluation of our proposal we have obtained successful results.

Hybrid system for plagiarism detection

The Internet boom in recent years has increased the interest in the field of plagiarism detection. A lot of documents are published on the Net everyday and anyone can access and plagiarize them. Of course, checking all cases of plagiarism manually is an unfeasible task. Therefore, it is necessary to create new systems that are able to automatically detect cases of plagiarism produced. In this paper, we introduce a new hybrid system for plagiarism detection which combines the advantages of the two main plagiarism detection techniques. This system consists of two analysis phases: the first phase uses an intrinsic detection technique which dismisses much of the text, and the second phase employs an external detection technique to identify the plagiarized text sections. With this combination we achieve a detection system which obtains accurate results and is also faster thanks to the prefiltering of the text.

Evaluating the robustness of EmotiBlog for sentiment analysis and opinion mining

Preliminary research demonstrated the EmotiBlog annotated corpus relevance as a Machine Learning resource to detect subjective data. In this paper we compare EmotiBlog with the JRC Quotes corpus in order to check the robustness of its annotation. We concentrate on its coarse-grained labels and carry out a deep Machine Learning experimentation also with the inclusion of lexical resources. The results obtained show a similarity with the ones obtained with the JRC Quotes corpus demonstrating the EmotiBlog validity as a resource for the SA task.

A comparative study of open domain and opinion question answering systems for factual and opinionated queries

The development of the Web 2.0 led to the birth of new textual genres such as blogs, reviews or forum entries. The increasing number of such texts and the highly diverse topics they discuss make blogs a rich source for analysis. This paper presents a comparative study on open domain and opinion QA systems. A collection of opinion and mixed fact-opinion questions in English is defined and two Question Answering systems are employed to retrieve the answers to these queries. The first one is generic, while the second is specific for emotions. We comparatively evaluate and analyze the systems’ results, concluding that opinion Question Answering requires the use of specific resources and methods.

EmotiBlog: a finer-grained and more precise learning of subjectivity expression models

The exponential growth of the subjective information in the framework of the Web 2.0 has led to the need to create Natural Language Processing tools able to analyse and process such data for multiple practical applications. They require training on specifically annotated corpora, whose level of detail must be fine enough to capture the phenomena involved. This paper presents EmotiBlog – a fine-grained annotation scheme for subjectivity. We show the manner in which it is built and demonstrate the benefits it brings to the systems using it for training, through the experiments we carried out on opinion mining and emotion detection. We employ corpora of different textual genres –a set of annotated reported speech extracted from news articles, the set of news titles annotated with polarity and emotion from the SemEval 2007 (Task 14) and ISEAR, a corpus of real-life self-expressed emotion. We also show how the model built from the EmotiBlog annotations can be enhanced with external resources. The results demonstrate that EmotiBlog, through its structure and annotation paradigm, offers high quality training data for systems dealing both with opinion mining, as well as emotion detection.

PHORA: a system to solve the anaphora in Spanish

In this paper we present a whole Natural Language Processing (NLP) system for Spanish. The core of this system is the parser, which uses the grammatical formalism Lexical-Functional Grammars (LFG). Another important component of this system is the anaphora resolution module. To solve the anaphora, this module contains a method based on linguistic information (lexical, morphological, syntactic and semantic), structural information (anaphoric accessibility space in which the anaphor obtains the antecedent) and statistical information. This method is based on constraints and preferences and solves pronouns and definite descriptions. Moreover, this system fits dialogue and non-dialogue discourse features. The anaphora resolution module uses several resources, such as a lexical database (Spanish WordNet) to provide semantic information and a POS tagger providing the part of speech for each word and its root to make this resolution process easier.