Using Twitter to learn about the autism community

Considering the raising socio-economic burden of autism spectrum disorder (ASD), timely and evidence-driven public policy decision making and communication of the latest guidelines pertaining to the treatment and management of the disorder is crucial. Yet evidence suggests that policy makers and medical practitioners do not always have a good understanding of the practices and relevant beliefs of ASD-afflicted individuals' carers who often follow questionable recommendations and adopt advice poorly supported by scientific data. The key goal of the present work is to explore the idea that Twitter, as a highly popular platform for information exchange, could be used as a data-mining source to learn about the population affected by ASD -- their behaviour, concerns, needs etc. To this end, using a large data set of over 11 million harvested tweets as the basis for our investigation, we describe a series of experiments which examine a range of linguistic and semantic aspects of messages posted by individuals interested in ASD. Our findings, the first of their nature in the published scientific literature, strongly motivate additional research on this topic and present a methodological basis for further work.Comment: Social Network Analysis and Mining, 201

Metaphor and Senses

The book deals with the synesthetic metaphors in Synamet – a semantically and grammatically annotated corpus. The texts included in the corpus are excerpted from blogs devoted to, among others, perfume, wine, beer, music, art, massage and wellness. The thesis presents a Conceptual Metaphor Theory (CMT) and frame-based analysis of synesthetic metaphors in Polish. Using data from the corpus, the book provides ample empirical support for embodiment in metaphor and internal logic of mappings between frames. The study proposes new models of verbal synesthesia in the corpus and calls into question a universality of hierarchy of senses. This book should be of interest to researchers working within cognitive linguistics, in particular metaphor theory, frame semantics, corpus linguistics, and sensory science

Variation in the Vowel System of Mišótika Cappadocian: Findings from Two Refugee Villages in Greec

This paper discusses changes in the vowel system of contemporary Mišótika, the Cappadocian variety originally spoken in Misti. We compare the speech of native speakers from two Cappadocian refugee communities and analyse the differences between the two, taking into consideration mechanisms of language contact and linguistic change, and also the social parameters that influence the dialectal system. The study is based on recordings of native speakers of Mišótika who live in two different villages, one in the prefecture of Kilkis (Neo Agioneri), and the other in Thessaloniki (Xirohori). Although these villages are very close to one another, they present two major differences. Neo Agioneri is a homogeneous village, whereas Xirohori is a mixed village, since not only Cappadocians but also other Greek-dialect speakers live there. 78 Another distinguishing characteristic between the two villages is the attitude of the inhabitants towards Mišótika. It seems that speakers from Neo Agioneri are more receptive to the use of the dialect. The inhabitants from Xirohori, by contrast, present a different attitude, reflecting the consequences of social stigmatization and linguistic attrition that their dialect has undergone after the population exchange of the 1920s. To conclude, the current vowel system of Mišótika seems to diverge significantly from the older one described by Dawkins (1916). At the same time, the preliminary findings of our research indicate that there are also differences in the phonological status of the vowels between speakers of the same linguistic system. Dawkins, R. M. 1916. Modern Greek in Asia Minor: a Study of the Dialects of Sílli, Cappadocia and Phárasa with Grammar, Texts, Translations and Glossary. Cambridge: Cambridge University Press

Machine-assisted mixed methods: augmenting humanities and social sciences with artificial intelligence

The increasing capacities of large language models (LLMs) present an unprecedented opportunity to scale up data analytics in the humanities and social sciences, augmenting and automating qualitative analytic tasks previously typically allocated to human labor. This contribution proposes a systematic mixed methods framework to harness qualitative analytic expertise, machine scalability, and rigorous quantification, with attention to transparency and replicability. 16 machine-assisted case studies are showcased as proof of concept. Tasks include linguistic and discourse analysis, lexical semantic change detection, interview analysis, historical event cause inference and text mining, detection of political stance, text and idea reuse, genre composition in literature and film; social network inference, automated lexicography, missing metadata augmentation, and multimodal visual cultural analytics. In contrast to the focus on English in the emerging LLM applicability literature, many examples here deal with scenarios involving smaller languages and historical texts prone to digitization distortions. In all but the most difficult tasks requiring expert knowledge, generative LLMs can demonstrably serve as viable research instruments. LLM (and human) annotations may contain errors and variation, but the agreement rate can and should be accounted for in subsequent statistical modeling; a bootstrapping approach is discussed. The replications among the case studies illustrate how tasks previously requiring potentially months of team effort and complex computational pipelines, can now be accomplished by an LLM-assisted scholar in a fraction of the time. Importantly, this approach is not intended to replace, but to augment researcher knowledge and skills. With these opportunities in sight, qualitative expertise and the ability to pose insightful questions have arguably never been more critical

Expertise and Knowledge in the Age of Personalized Media: The Case of @anysports.faceonline Blog in the Period from 2018 to 2019

Digital age, that we are living in, enables us to instantly access great volumes of various information. The way we acquire, create and distribute knowledge is a subject to continuous transformation caused by the rapid growth of digital content and tools. Nowadays, more and more people give their own contribution in digital knowledge environment by producing and sharing their digital content. This thesis considers the impact that digital culture has put on the way we consume and create knowledge and establish the image of trustworthy expert in a certain field. This research is a case study of the Instagram account @anysports.faceonline. It represents a qualitative research aiming to analyze visual rhetoric and knowledge representation in the @anysports.faceonline blog in order to examine the mechanics of impression management, concerning the establishment and gaining acknowledgement of professionalism / expertise within online environment. By visual rhetoric is meant, in the first place, a form of visual communication the influencer uses. It involves the visual structure, displaying of information, color usage and designing of self-representation. Moreover, this research is not constrained in cultural history only, it refers to other fields such as psychology, sociology, marketing, media and gender studies. However, in order to explain the chosen visual strategies, the object of the research is, firstly, put into a broad cultural context

From icon to naturalised icon:a linguistic analysis of media representations of the BP Deepwater Horizon crisis

This research explores how news media reports construct representations of a business crisis through language. In an innovative approach to dealing with the vast pool of potentially relevant texts, media texts concerning the BP Deepwater Horizon oil spill are gathered from three different time points: immediately after the explosion in 2010, one year later in 2011 and again in 2012. The three sets of 'BP texts' are investigated using discourse analysis and semi-quantitative methods within a semiotic framework that gives an account of language at the semiotic levels of sign, code, mythical meaning and ideology. The research finds in the texts three discourses of representation concerning the crisis that show a movement from the ostensibly representational to the symbolic and conventional: a discourse of 'objective factuality', a discourse of 'positioning' and a discourse of 'redeployment'. This progression can be shown to have useful parallels with Peirce's sign classes of Icon, Index and Symbol, with their implied movement from a clear motivation by the Object (in this case the disaster events), to an arbitrary, socially-agreed connection. However, the naturalisation of signs, whereby ideologies are encoded in ways of speaking and writing that present them as 'taken for granted' is at its most complete when it is least discernible. The findings suggest that media coverage is likely to move on from symbolic representation to a new kind of iconicity, through a fourth discourse of 'naturalisation'. Here the representation turns back towards ostensible factuality or iconicity, to become the 'naturalised icon'. This work adds to the study of media representation a heuristic for understanding how the meaning-making of a news story progresses. It offers a detailed account of what the stages of this progression 'look like' linguistically, and suggests scope for future research into both language characteristics of phases and different news-reported phenomena

Real-Time Event Analysis and Spatial Information Extraction From Text Using Social Media Data

Since the advent of websites that enable users to participate and interact with each other by sharing content in different forms, a plethora of possibly relevant information is at scientists\u27 fingertips. Consequently, this thesis elaborates on two distinct approaches to extract valuable information from social media data and sketches out the potential joint use case in the domain of natural disasters