Multiword expressions

Multiword expressions (MWEs) are a challenge for both the natural language applications and the linguistic theory because they often defy the application of the machinery developed for free combinations where the default is that the meaning of an utterance can be predicted from its structure. There is a rich body of primarily descriptive work on MWEs for many European languages but comparative work is little. The volume brings together MWE experts to explore the benefits of a multilingual perspective on MWEs. The ten contributions in this volume look at MWEs in Bulgarian, English, French, German, Maori, Modern Greek, Romanian, Serbian, and Spanish. They discuss prominent issues in MWE research such as classification of MWEs, their formal grammatical modeling, and the description of individual MWE types from the point of view of different theoretical frameworks, such as Dependency Grammar, Generative Grammar, Head-driven Phrase Structure Grammar, Lexical Functional Grammar, Lexicon Grammar

Rhetorics of Hope and Outrage: Emotion and Cynicism in the Coverage the Schengen Accession

Discourses on European integration and Euroscepticism have benefitted from increased interest after Brexit. Researchers point out that there is a great variance from one national context to another and that there is a gap in the literature concerning non-elite discourses and perspectives from Central and Eastern European countries such as Romania. The Eurobarometer findings of early 2023 indicate a shift in Romanian public opinion towards Euroscepticism. To better understand the potential causes for these shifts, we approach the politicisation of the issue in Romania through an analysis of online news headlines and related social media news sharing metadata. In the aftermath of the decision not to accept Romania and Bulgaria, this research investigates shifts in the media framing of the Schengen issue and EU over two months (from October 15 to December 15, 2022) in the 14 most accessed Romanian online news sites (with more than 10 million visits per month). Quantitative analysis of news headlines (N = 3,362) shows that the coverage focuses on Romanian politicians in power and emphasises conflict. Furthermore, the analysis of the interactions produced by news sharing of the analysed sample shows the impact of the political rhetoric encouraging the boycotting of Austrian companies in retaliation for the denial of Schengen Area accession: scapegoating and disenchantment with politics and politicians. The two-step approach used and results that use Facebook interactions as indicators of public resonance of politicisation and strategic framing may be replicated in future research

Different valuable tools for Arabic sentiment analysis: a comparative evaluation

Arabic Natural language processing (ANLP) is a subfield of artificial intelligence (AI) that tries to build various applications in the Arabic language like Arabic sentiment analysis (ASA) that is the operation of classifying the feelings and emotions expressed for defining the attitude of the writer (neutral, negative or positive). In order to work on ASA, researchers can use various tools in their research projects without explaining the cause behind this use, or they choose a set of libraries according to their knowledge about a specific programming language. Because of their libraries' abundance in the ANLP field, especially in ASA, we are relying on JAVA and Python programming languages in our research work. This paper relies on making an in-depth comparative evaluation of different valuable Python and Java libraries to deduce the most useful ones in Arabic sentiment analysis (ASA). According to a large variety of great and influential works in the domain of ASA, we deduce that the NLTK, Gensim and TextBlob libraries are the most useful for Python ASA task. In connection with Java ASA libraries, we conclude that Weka and CoreNLP tools are the most used, and they have great results in this research domain

Insights from a multi-lingual perspective

Multiword expressions (MWEs) are a challenge for both the natural language applications and the linguistic theory because they often defy the application of the machinery developed for free combinations where the default is that the meaning of an utterance can be predicted from its structure. There is a rich body of primarily descriptive work on MWEs for many European languages but comparative work is little. The volume brings together MWE experts to explore the benefits of a multilingual perspective on MWEs. The ten contributions in this volume look at MWEs in Bulgarian, English, French, German, Maori, Modern Greek, Romanian, Serbian, and Spanish. They discuss prominent issues in MWE research such as classification of MWEs, their formal grammatical modeling, and the description of individual MWE types from the point of view of different theoretical frameworks, such as Dependency Grammar, Generative Grammar, Head-driven Phrase Structure Grammar, Lexical Functional Grammar, Lexicon Grammar

Developmental and stylistic consistency in selected choral works of Felicia Donceanu (b. 1931)

The music of Felicia Donceanu (b. 1931) is well known by music scholars in Romania. Donceanu's work has won numerous accolades including honorable mention at the International Composition Competition in Mannheim, Germany, in 1961, the prize of the Union of Composers and Musicologists of Romania seven times between 1983 and 1997, and the George Enescu prize in 1984. Donceanu's colleagues regard her Romanian-language art songs to be among the finest examples of the genre. Donceanu has composed for nearly every instrumental genre, but solo vocal and choral compositions comprise the majority of her output. Paula Boire discussed Donceanu's art songs in the four-volume text, A Comprehensive Study of Romanian Art Song, but Donceanu's choral works remain largely unexplored. Donceanu's first choral compositions date from 1968, and her choral oeuvre includes more than forty compositions written over several decades. Despite this, she considers dates of composition to be irrelevant and has stated that her works neither exhibit stylistic development nor fit into creative periods. Analyses of five representative choral compositions: "Inscriptie" from Trei poeme corale (1968), Rodul bun (1982), Ritual de Statornicie (1987), Tatal nostru (1990), and Clopote la soroc (1996), reveal this consistency of style as it occurs in Donceanu's choral works

Building Phrase Polarity Lexicons for Sentiment Analysis

Many approaches to sentiment analysis benefit from polarity lexicons. Most polarity lexicons include a list of polar (positive/negative) words, and sentiment analysis systems attempt to capture the occurrence of those words in text using polarity lexicons. Although there exist some polarity lexicons in many natural languages, most languages suffer from the lack of phrase polarity lexicons. Phrases play an important role in sentiment analysis because the polarity of a phrase cannot always be estimated based on the polarity of its parts. In this work, a hybrid approach is proposed for building phrase polarity lexicons which is experimented on Turkish as a low-resource language. The obtained classification accuracies in extracting and classifying phrases as positive, negative, or neutral, approve the effectiveness of the proposed methodology

Extrapolating Subjectivity Research to Other Languages

Socrates articulated it best, "Speak, so I may see you." Indeed, language represents an invisible probe into the mind. It is the medium through which we express our deepest thoughts, our aspirations, our views, our feelings, our inner reality. From the beginning of artificial intelligence, researchers have sought to impart human like understanding to machines. As much of our language represents a form of self expression, capturing thoughts, beliefs, evaluations, opinions, and emotions which are not available for scrutiny by an outside observer, in the field of natural language, research involving these aspects has crystallized under the name of subjectivity and sentiment analysis. While subjectivity classification labels text as either subjective or objective, sentiment classification further divides subjective text into either positive, negative or neutral. In this thesis, I investigate techniques of generating tools and resources for subjectivity analysis that do not rely on an existing natural language processing infrastructure in a given language. This constraint is motivated by the fact that the vast majority of human languages are scarce from an electronic point of view: they lack basic tools such as part-of-speech taggers, parsers, or basic resources such as electronic text, annotated corpora or lexica. This severely limits the implementation of techniques on par with those developed for English, and by applying methods that are lighter in the usage of text processing infrastructure, we are able to conduct multilingual subjectivity research in these languages as well. Since my aim is also to minimize the amount of manual work required to develop lexica or corpora in these languages, the techniques proposed employ a lever approach, where English often acts as the donor language (the fulcrum in a lever) and allows through a relatively minimal amount of effort to establish preliminary subjectivity research in a target language