The present paper aims to report on the preliminary findings from the initial stages of ongoing research on hate speech in Lithuanian online comments. Comments are marked strongly by such phenomena as flaming and trolling; therefore, in this genre we can expect a high degree of hostility, obscenity, high incidence of insults and aggressive lexis, which can inflict harm to individuals or organizations. The goal of the current research is thus to make an attempt to identify some features of verbal (...) aggression in Lithuanian by applying the principles and instruments of corpus linguistics, which proved to be a useful approach when dealing with such issues as trolling. It is expected that further analysis of those features will help to identify and define formal linguistic criteria that could facilitate identification of hate speech in public discourse. The data has been obtained from the Lithuanian corpus of user-generated comments collected from one major Lithuanian portal, www.delfi.lt. The corpus consists of all the comments posted in the year 2014 and in total includes 17,909 comments, which make up 1,160,109 words. For the initial data analysis, linguistic aspects, such as wordlists, collocations, and formulaic language, were analysed by using the AntConc software. The interpretations of the results are still very tentative, but what the initial findings show is that overt aggression does not feature among the most frequent and most salient features of comments. Aggression is, in our data, indirectly expressed through creative language use, which can mainly be studied through qualitative analysis. (shrink)

The paper investigates various definitions of the concept of opinion as opposed to factual or evidence-based statements and proposes a taxonomy of opinions expressed in English as identified in selected social media. A discussion situates opinions in the realm of pragmatics and reaches to philosophy of language and cognitive science. The research methodology combines a thorough linguistic analysis of opinions, proposing their multifaceted taxonomy with the automatically generated lexical embeddings of positive and negative lexicon acquired from the analysed opinionated texts. (...) As proposed, the definition of the concept of opinion is best apprehended when looked upon in terms of an opinion event, with a number of necessary conditions on the one hand, and those that are characteristic of an explicit opinion prototype on the other. Lists of opinion discourse markers show their preferential uses either in positive or negative opinionated texts; however, no sets of necessary and/or sufficient opinion markers properties have been acquired from the analysed texts. The conclusions indicate a polysemous understanding of naturally occurring social media opinionated texts and a definitional flexibility of the boundaries around lexical positive and negative types of opinion markers. (shrink)

Vague References to Quantities as a Face-Saving Strategy in Teacher-Student Interaction The main focus of the present paper is to show how vague language categories can function as a face-saving strategy. The observations made in this article are based on the analysis of one category of vague language, that is, quantifiers in British and American spoken academic discourse. The data used for the present investigation have been obtained from two corpora: the sub-corpus of educational events of the British National Corpus (...) and the Michigan Corpus of Academic Spoken Discourse. The results suggest that quantifiers as a face-saving strategy are used when self-criticism or criticism towards others is expressed. They are often employed in apologies, promises, self-justifications, when giving advice and in cases of uncertainty. Both students and teachers use quantifiers in these situations, but in teachers' speech they are of special importance, since teachers, if they want to maintain their authority, are especially conscious of their positive face. Paucal quantifiers especially frequently function as a face-saving device since they have a mitigating effect. The use of quantifiers as mitigators is especially evident in those instances where they occur in negative contexts. Such instances demonstrate that the main difference between the two varieties under investigation is that in BE quantifiers significantly more frequently function as mitigators. Finally, it has been observed that quantifiers frequently occur alongside other means of self-distancing and face-saving in both varieties. (shrink)