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The purpose of this paper is to explore the differences between consumer motives regarding purchase of traditional food in two European countries (Croatia and Austria) with a different history and development in regards to traditional and/or regional food.

A word association test and soft laddering interviews were used to elicit consumers’ perception and purchasing motives for traditional food. Additionally, the questionnaire contained socio-demographics and questions about shopping habits concerning traditional food. Semi-structured, individual, face-to-face interviews were performed with 31 Croatian and 28 Austrian respondents.

The most frequent associations/definition in both countries refers to heritage (food of generations) and elaboration (traditional receipt). The meaning of traditional food is for both samples positive. Hierarchical value maps for both countries contain ladders standing for health or support of local farmers. Additionally, the Austrians connect traditional food with environmental friendly production while for the Croatians sentimental hedonism ladder starts with perception of traditional food as a mean to connect with the childhood.

The findings can be used by traditional food producers in order to better understand consumers’ motives and accordingly adapt their marketing strategies.

This is the first work which uses free association test and laddering interviews to reveal consumers perception and motives for purchase of traditional food both in Croatia as well as in Austria.

To propose a categorization of the different conflation procedures at the two basic approaches, non‐linguistic and linguistic techniques, and to justify the application of normalization methods within the framework of linguistic techniques.

Presents a range of term conflation methods, that can be used in information retrieval. The uniterm and multiterm variants can be considered equivalent units for the purposes of automatic indexing. Stemming algorithms, segmentation rules, association measures and clustering techniques are well evaluated non‐linguistic methods, and experiments with these techniques show a wide variety of results. Alternatively, the lemmatisation and the use of syntactic pattern‐matching, through equivalence relations represented in finite‐state transducers (FST), are emerging methods for the recognition and standardization of terms.

The survey attempts to point out the positive and negative effects of the linguistic approach and its potential as a term conflation method.

Outlines the importance of FSTs for the normalization of term variants.

Most educational assessments tend to be constructed in a close-ended format, which is easier to score consistently and more affordable. However, recent work has leveraged computation text methods from the information sciences to make open-ended measurement more effective and reliable for older students. The purpose of this study is to determine whether models used by computational text mining applications need to be adapted when used with samples of elementary-aged children.

This study introduces domain-adapted semantic models for child-specific text analysis, to allow better elementary-aged educational assessment. A corpus compiled from a multimodal mix of spoken and written child-directed sources is presented, used to train a children’s language model and evaluated against standard non-age-specific semantic models.

Child-oriented language is found to differ in vocabulary and word sense use from general English, while exhibiting lower gender and race biases. The model is evaluated in an educational application of divergent thinking measurement and shown to improve on generalized English models.

The findings demonstrate the need for age-specific language models in the growing domain of automated divergent thinking and strongly encourage the same for other educational uses of computation text analysis by showing a measurable difference in the language of children.

Understanding children’s language more representatively in automated educational assessment allows for more fair and equitable testing. Furthermore, child-specific language models have fewer gender and race biases.

Research in computational measurement of open-ended responses has thus far used models of language trained on general English sources or domain-specific sources such as textbooks. To the best of the authors’ knowledge, this paper is the first to study age-specific language models for educational assessment. In addition, while there have been several targeted, high-quality corpora of child-created or child-directed speech, the corpus presented here is the first developed with the breadth and scale required for large-scale text modeling.

The purpose of this study is to employ the collage technique, an unstructured qualitative association instrument, with respect to place branding initiatives and to uncover internal stakeholders' perceptions of the region or destination.

The first part presents a general framework of brand and destination branding in the field of tourism research. The empirical study was carried out in selected Alpine tourism destinations. In the first stage the authors identified the main representatives of stakeholders in two Austrian tourism destinations. In the second, the collage technique was used to obtain stakeholders' perceptions of the tourism destination brand.

The findings reveal that different internal stakeholders trace different perceptions of tourism places and illustrate the importance of using the collage as a technique to explore the various identities of a place.

It is argued that internal destination stakeholders do not share the same brand perception of the destination brand and they do not share a common identity, which is communicated through the destination management organisations (DMOs). However, more research is needed to support these findings as the study is limited by its sample size and focus on the Alpine region of Tyrol, Austria.

The results suggest that DMOs should establish better identities within their destination. In particular, they must consider that the collage is a very important technique in communicating the desired brand identity to internal destination stakeholders.

This paper seeks to clarify the effectiveness of the collage method as a tool to measure stakeholders' identities of selected tourism destinations. The paper demonstrates the importance of employing different association methods (word or picture) in recognizing stakeholders' knowledge and opinions of destinations as a primary step in analyzing stakeholders' brand identity perception.

Though the circular economy (CE) is a current buzzword, this still lacks a precise definition. In the absence of a clear notion of what that term includes, actions taken by the government and companies may not be well informed. In particular, those actions need to consider what people mean when people talk about the CE, either to refocus people's decisions or to undertake a more effective communications strategy.

Since people voice people's opinions mainly through social media nowadays, special attention has to be paid to discussions on those media. In this paper, the authors focus on Twitter as a popular social platform to deliver one's thoughts quickly and fast. The authors' research aim is to get the perceptions of people about the CE. After collecting more than 100,000 tweets over 16 weeks, the authors analyse those tweets to understand the public discussion about the CE. The authors conduct a frequency analysis of the most recurring words, including the words' association with other words in the same context and categorise them into a set of topics.

The authors show that the discussion focuses on the usage of resources and materials that heavily endanger sustainability, i.e. carbon and plastic and the harmful habit of wasting. On the other hand, the two most common good practices associated with the CE and sustainability emerge as recycling and reuse (the latter being mentioned far less). Also, the business side of the CE appears to be relevant.

The outcome of this analysis can drive suitable communication strategies by which companies and governments interested in the development of the CE can understand what is actually discussed on social media and call for the attention.

This paper addresses the lack of a standard definition the authors highlighted in the Introduction. The results confirm that people understand CE by looking both at CE's constituent activities and CE's expected consequences, namely the reduction of waste, the transition to a green economy free of plastic and other pollutants and the improvement of the world climate.

This explorative research aims at examining the social representation of psychosocial training in NPOs managers.

An adopted multiple research approach was adopted to analyse a corpus of qualitative data. A detailed semi‐structured interview was administered to 122 senior managers of as many Italian NPOs. Interviews were analyzed using different techniques of content analysis and, run through the software T‐Lab (analysis of word occurrence and co‐word mapping, analysis of Markovian sequences).

Italian NPOs' organizational culture seem to be action‐oriented and self‐referral, rather than knowledge‐oriented. Training is not considered as a tool for strategic management of HR. Senior managers are mainly self‐taught, trained on‐the‐job and, lack of a proper competence on HR management.

The group reached is a convenience sample and not a statistical representative sample.

The paper suggests that intellectual capital can be an effective tool to address Italian NPOs self‐referential knowledge and overcome their gaps in strategic management of human resources.

NPOs' senior manager training has rarely been addressed; in addition, the adopted methodology mixes different techniques of analysis.

To propose a comprehensive and semi‐automatic method for constructing or updating knowledge organization tools such as thesauri.

The paper proposes a comprehensive methodology for thesaurus construction and maintenance combining shallow NLP with a clustering algorithm and an information visualization interface. The resulting system TermWatch, extracts terms from a text collection, mines semantic relations between them using complementary linguistic approaches and clusters terms using these semantic relations. The clusters are mapped onto a 2D using an integrated visualization tool.

The clusters formed exhibit the different relations necessary to populate a thesaurus or ontology: synonymy, generic/specific and relatedness. The clusters represent, for a given term, its closest neighbours in terms of semantic relations.

This could change the way in which information professionals (librarians and documentalists) undertake knowledge organization tasks. TermWatch can be useful either as a starting point for grasping the conceptual organization of knowledge in a huge text collection without having to read the texts, then actually serving as a suggestive tool for populating different hierarchies of a thesaurus or an ontology because its clusters are based on semantic relations.

This lies in several points: combined use of linguistic relations with an adapted clustering algorithm, which is scalable and can handle sparse data. The paper proposes a comprehensive approach to semantic relations acquisition whereas existing studies often use one or two approaches. The domain knowledge maps produced by the system represents an added advantage over existing approaches to automatic thesaurus construction in that clusters are formed using semantic relations between domain terms. Thus while offering a meaningful synthesis of the information contained in the original corpus through clustering, the results can be used for knowledge organization tasks (thesaurus building and ontology population) The system also constitutes a platform for performing several knowledge‐oriented tasks like science and technology watch, textmining, query refinement.

The purpose of this paper is to analyse how the media addresses entrepreneurship and to identify the attributes linked to this phenomenon.

The sample is defined in terms of a linguistic corpus comprised of content related to entrepreneurship drawn from the digital editions of the three most important Spanish economic newspapers for the period 2010–2017. Word association and co-occurrence analyses were carried out. Further, a non-supervised clustering process was used as the basis for a thematic analysis.

Correspondence between social and media patterns related to the entrepreneurship phenomenon is revealed by the results. It is shown how attributes such as “success”, “innovation”, “ecosystem” and “woman” appear as very relevant and are linked to different co-occurrence scenarios. Relevant thematic groups are also identified related to lexical associations such as innovation, digital economy and public policies linked to entrepreneurship.

It is important to emphasise that this study has identified and explored relationships between words, but not their evolution. Furthermore, conclusions cannot be drawn concerning whether there are differences in how each newspaper has dealt with entrepreneurship because of the way the corpus was constructed.

The study provides empirical evidence that helps to identify the way media approaches entrepreneurship. The authors carried out the analysis on the media contents and not on the perception of the public on the phenomenon.

This chapter details how engaging students in digital comics creation might support adolescents in strengthening their narrative writing capabilities. This chapter first provides a more detailed explanation of the micro and macrostructural elements involved in narrative production. Second, the chapter provides an introduction to comics and important design features. The authors also illuminate the complexity of multimodal texts (texts that combine images and words) and link visual narrative pedagogy and curriculum to classroom equity and accessibility. Across these opening sections, academic standards are referenced to show how the comics medium aligns with national visions of what robust English Language Arts education entails. The chapter concludes with descriptions of specific pedagogical strategies and digital comic-making tools that teachers and interventionists might explore with students within various classroom contexts. Examples of digital comics designed using various web tools are also shared.

In this paper the main emphasis will be upon mechanized methods of documentation which work with a natural language input. These are systems in which the basic sources are read in to the machines in their pristine form, unindexed, unclassified and unabridged. The paper will first set out to correct some current misconceptions about mechanical methods. It will then consider the tasks which a modern digital computer can perform, and each will be examined in the context of documentation.