"Virtual word of mouth":a case for the adaptation of existing word of mouth theory to virtual community environments

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Methodology for Language Analysis and Generation in Closed Domains: Pharmaceutical Leaflet

The best results in the application of computer science systems to automatic translation are obtained in word processing when texts pertain to specific thematic areas, with structures well defined and a concise and limited lexicon. In this article we present a plan of systematic work for the analysis and generation of language applied to the field of pharmaceutical leaflet, a type of document characterized by format rigidity and precision in the use of lexicon. We propose a solution based in the use of one interlingua as language pivot between source and target languages; we are considering Spanish and Arab languages in this case of application.

On the F word:a corpus-based analysis of the media representation of feminism in British and German press discourse, 1990-2009

Research in social psychology has shown that public attitudes towards feminism are mostly based on stereotypical views linking feminism with leftist politics and lesbian orientation. It is claimed that such attitudes are due to the negative and sexualised media construction of feminism. Studies concerned with the media representation of feminism seem to confirm this tendency. While most of this research provides significant insights into the representation of feminism, the findings are often based on a small sample of texts. Also, most of the research was conducted in an Anglo-American setting. This study attempts to address some of the shortcomings of previous work by examining the discourse of feminism in a large corpus of German and British newspaper data. It does so by employing the tools of Corpus Linguistics. By investigating the collocation profiles of the search term feminism, we provide evidence of salient discourse patterns surrounding feminism in two different cultural contexts. © The Author(s) 2012.

Improving distributed representation of word sense via WordNet Gloss composition and context clustering

In recent years, there has been an increas-ing interest in learning a distributed rep-resentation of word sense. Traditional context clustering based models usually require careful tuning of model parame-ters, and typically perform worse on infre-quent word senses. This paper presents a novel approach which addresses these lim-itations by first initializing the word sense embeddings through learning sentence-level embeddings from WordNet glosses using a convolutional neural networks. The initialized word sense embeddings are used by a context clustering based model to generate the distributed representations of word senses. Our learned represen-tations outperform the publicly available embeddings on 2 out of 4 metrics in the word similarity task, and 6 out of 13 sub tasks in the analogical reasoning task.

Automatic Discovery of Word Semantic Relations

In this paper, we propose an unsupervised methodology to automatically discover pairs of semantically related words by highlighting their local environment and evaluating their semantic similarity in local and global semantic spaces. This proposal di®ers from previous research as it tries to take the best of two different methodologies i.e. semantic space models and information extraction models. It can be applied to extract close semantic relations, it limits the search space and it is unsupervised.

A gloss composition and context clustering based distributed word sense representation model

In recent years, there has been an increasing interest in learning a distributed representation of word sense. Traditional context clustering based models usually require careful tuning of model parameters, and typically perform worse on infrequent word senses. This paper presents a novel approach which addresses these limitations by first initializing the word sense embeddings through learning sentence-level embeddings from WordNet glosses using a convolutional neural networks. The initialized word sense embeddings are used by a context clustering based model to generate the distributed representations of word senses. Our learned representations outperform the publicly available embeddings on half of the metrics in the word similarity task, 6 out of 13 sub tasks in the analogical reasoning task, and gives the best overall accuracy in the word sense effect classification task, which shows the effectiveness of our proposed distributed distribution learning model.

Resisting the final word:challenging stale media and policy representations of students’ performative technological encounters in university education

This article explores powerful, constraining representations of encounters between digital technologies and the bodies of students and teachers, using corpus-based Critical Discourse Analysis (CDA). It discusses examples from a corpus of UK Higher Education (HE) policy documents, and considers how confronting such documents may strengthen arguments from educators against narrow representations of an automatically enhanced learning. Examples reveal that a promise of enhanced ‘student experience’ through information and communication technologies internalizes the ideological constructs of technology and policy makers, to reinforce a primary logic of exchange value. The identified dominant discursive patterns are closely linked to the Californian ideology. By exposing these texts, they provide a form of ‘linguistic resistance’ for educators to disrupt powerful processes that serve the interests of a neoliberal social imaginary. To mine this current crisis of education, the authors introduce productive links between a Networked Learning approach and a posthumanist perspective. The Networked Learning approach emphasises conscious choices between political alternatives, which in turn could help us reconsider ways we write about digital technologies in policy. Then, based on the works of Haraway, Hayles, and Wark, a posthumanist perspective places human digital learning encounters at the juncture of non-humans and politics. Connections between the Networked Learning approach and the posthumanist perspective are necessary in order to replace a discourse of (mis)representations with a more performative view towards the digital human body, which then becomes situated at the centre of teaching and learning. In practice, however, establishing these connections is much more complex than resorting to the typically straightforward common sense discourse encountered in the Critical Discourse Analysis, and this may yet limit practical applications of this research in policy making.

A mérsékelt iszlamista mozgalmak szerepe az "arab tavaszt" követő politikai átmenetben (The Role of Moderate Islamist Movements in the Political Transition Following the Arab Spring)

Up to January 2011 authoritarian political regimes in the Middle East had widely been considered stable due to the armed forces, the underdeveloped political institutions, the economic embeddedness of the regimes, the neo-patrimonial structure of the Arab societies and, eventually the characteristics of Islam. Middle Eastern political systems are often considered to belong to a special sub-group of non-democratic regimes called “liberalized autocracies”. The 2011 events show that there is a new, as yet non-defined political structure emerging. Although there are different interpretations of the developments, there is a consensus on the determinant role of the Islamist organizations in the development of the new political structure. The results of the Egyptian and Tunisian parliamentary elections show that the secular political parties could not attract the public, while in Tunisia the long forbidden Hizb an-Nahda could form a government. In Egypt Hizb al-Hurriya established by the Muslim Brotherhood in 2011 won almost half of the parliamentary mandates, and to a great surprise, the Salafi Hizb an-Nour also received 24.3% of the votes. On the basis of the above developments the thesis of the Islamist re-organization of the Middle East, i.e. of a new wave of Islamism was elaborated, according to which the main political winners of the revolts in the Arab countries are the Islamist organizations, which could step in and fill in the political vacuum. While some speak of an Islamist autumn or Islamist winter as the result of the Arab Spring, others prefer the term Islamic revolutions.

Az on-line szájreklám (electronic word-of-mouth) jellemzői a marketingkommunikáció szempontjából

Az on-line térben a vállalatok elveszítik a hagyományos tömegkommunikációban gyakorolt kontrollt, ugyanakkor kommunikációs szerepükből fakadóan megmarad egy ráhatási képességük. Ahhoz azonban, hogy e ráhatási képességet ki tudják használni, megfelelő eszközöket kell alkalmazniuk, amelyek közül az egyik lehetőség az on-line szájreklám (electronic word-of-mouth, e-WOM). A cikk egy szakirodalmi összefoglalót nyújt az e-WOM-ról, kitérve arra, hogy milyen új kommunikációs kihívásokkal és lehetőségekkel néznek szembe a fogyasztók és a vállalatok az on-line térben. Továbbá hogyan értelmezhető az e-WOM, milyen alapvető tulajdonságokkal és a fogyasztókra, valamint a vállalatokra gyakorolt hatásokkal rendelkezik. Ezen ismeretekre építve pedig a szerző bemutatja azt is, hogy a fogyasztók között zajló on-line kommunikáció (vagyis az e-WOM) hogyan integrálható a marketingkommunikációs tevékenységbe.

The effects of word prediction and text-to-speech technologies on the narrative writing skills of students with specific learning disabilities

This study investigated the effects of word prediction and text-to-speech on the narrative composition writing skills of 6, fifth-grade Hispanic boys with specific learning disabilities (SLD). A multiple baseline design across subjects was used to explore the efficacy of word prediction and text-to-speech alone and in combination on four dependent variables: writing fluency (words per minute), syntax (T-units), spelling accuracy, and overall organization (holistic scoring rubric). Data were collected and analyzed during baseline, assistive technology interventions, and at 2-, 4-, and 6-week maintenance probes. ^ Participants were equally divided into Cohorts A and B, and two separate but related studies were conducted. Throughout all phases of the study, participants wrote narrative compositions for 15-minute sessions. During baseline, participants used word processing only. During the assistive technology intervention condition, Cohort A participants used word prediction followed by word prediction with text-to-speech. Concurrently, Cohort B participants used text-to-speech followed by text-to-speech with word prediction. ^ The results of this study indicate that word prediction alone or in combination with text-to-speech has a positive effect on the narrative writing compositions of students with SLD. Overall, participants in Cohorts A and B wrote more words, more T-units, and spelled more words correctly. A sign test indicated that these perceived effects were not likely due to chance. Additionally, the quality of writing improved as measured by holistic rubric scores. When participants in Cohort B used text-to-speech alone, with the exception of spelling accuracy, inconsequential results were observed on all dependent variables. ^ This study demonstrated that word prediction alone or in combination assists students with SLD to write longer, improved-quality, narrative compositions. These results suggest that word prediction or word prediction with text-to-speech be considered as a writing support to facilitate the production of a first draft of a narrative composition. However, caution should be given to the use of text-to-speech alone as its effectiveness has not been established. Recommendations for future research include investigating the use of these technologies in other phases of the writing process, with other student populations, and with other writing styles. Further, these technologies should be investigated while integrated into classroom composition instruction. ^

Student Knowledge and Perceptions of Islam and the Arab and Muslim World

Students’ knowledge and perceptions of Islam and the Arab and Muslim world were assessed at three schools to evaluate the effectiveness of the current pedagogy and curriculum. Results show that students have little knowledge of the subject, say that they get most of their information from their teachers, have fairly positive perceptions of Islam and the Arab and Muslim world, and have suggestions to improve the curriculum.

The Effects of the Word of Wisdom Meditation Technique on the Development of Executive Function Skills in Early Childhood Education

This theory-based paper examines the definition of Executive Functioning (EF) skills, their importance in the early childhood classroom and how to aid in their natural development. The Word of Wisdom meditation technique is considered as a viable alternative to increase the natural development of EF skills in early childhood.

Do Syllable Count and Word Frequency Differ Significantly in Easy and Difficult Reading Comprehension Items?

This study investigated the effect of the number of syllables and the word frequency of the words in the reading passages, the question stems, and the answer options of easy and difficult reading comprehension items. Significant differences were found for the easy and difficult items.

Vocabulary learning through use of the picture-word inductive model for young English learners in China: A mixed methods examination using Cognitive Load Theory

English has been taught as a core and compulsory subject in China for decades. Recently, the demand for English in China has increased dramatically. China now has the world's largest English-learning population. The traditional English-teaching method cannot continue to be the only approach because it merely focuses on reading, grammar and translation, which cannot meet English learners and users' needs (i.e., communicative competence and skills in speaking and writing). ^ This study was conducted to investigate if the Picture-Word Inductive Model (PWIM), a new pedagogical method using pictures and inductive thinking, would benefit English learners in China in terms of potential higher output in speaking and writing. With the gauge of Cognitive Load Theory (CLT), specifically, its redundancy effect, I investigated whether processing words and a picture concurrently would present a cognitive overload for English learners in China. ^ I conducted a mixed methods research study. A quasi-experiment (pretest, intervention for seven weeks, and posttest) was conducted using 234 students in four groups in Lianyungang, China (58 fourth graders and 57 seventh graders as an experimental group with PWIM and 59 fourth graders and 60 seventh graders as a control group with the traditional method). No significant difference in the effects of PWIM was found on vocabulary acquisition based on grade levels. Observations, questionnaires with open-ended questions, and interviews were deployed to answer the three remaining research questions. A few students felt cognitively overloaded when they encountered too many writing samples, too many new words at one time, repeated words, mismatches between words and pictures, and so on. Many students listed and exemplified numerous strengths of PWIM, but a few mentioned weaknesses of PWIM. The students expressed the idea that PWIM had a positive effect on their English teaching. ^ As integrated inferences, qualitative findings were used to explain the quantitative results that there were no significant differences of the effects of the PWIM between the experimental and control groups in both grade levels, from four contextual aspects: time constraints on PWIM implementation, teachers' resistance, how to use PWIM and PWIM implemented in a classroom over 55 students.^