In recent years there has been an increasing amount of research on social cognition. Though the involved disciplines are very different, it seems that they have a common goal: to understand if social cognition is what characterizes us as a species, what makes us extremely different from other animal species. We can say then that the background question of recent studies in cognitive sciences sounds like this: is human cognition marked out by our social skills? According to the most popular perspective in current cognitive sciences, the key of our uniqueness would stay in our peculiar form of shared intentionality, in other words, in our natural inclination to cooperate. It would be a distinctive kind of sociality that makes our species so different from the others. This thesis is grounded on two premises: nothing, in the animal world, compares to our ability to cooperate, and this difference lies just in our peculiar form of social cognition.
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The aim of this study is to explore the possibility of identifying speaker stance in discourse, provide an analytical resource for it and an evaluation of the level of agreement across speakers. We also explore to what extent language users agree about what kind of stances are expressed in natural language use or whether their interpretations diverge. In order to perform this task, a comprehensive cognitive-functional framework of ten stance categories was developed based on previous work on speaker stance in the literature.
An analytical protocol and interface Active Learning and Visual Analytics for the annotations was set up and the data were independently annotated by two annotators. The annotation procedure, the annotation agreements and the co-occurrence of more than one stance in the utterances are described and discussed. The careful, analytical annotation process has returned satisfactory inter- and intra-annotation agreement scores, resulting in a gold standard corpus, the final version of the BBC.
Communication between humans is never completely neutral in the sense that no particular perspective or selection of information is employed. Speakers take stance when interacting with other people. They make assessments and they position themselves in relation to other interlocutors to mark their standpoint Englebretson Speaker contributions come with stances expressed in a range of different ways that may convey more than one stance in different contexts, and there may be more than one stance expression in the same sentence or utterance.
There are cases of expressions of stance such as might, definitely, I am sure that that are treated as expressions of stance in the literature, but there are also types of constructions that might or might not be included in the category of speaker stance.
Utterances of this kind are pervasive in language use and make the study of stance in real communication intriguing, but also methodologically challenging. A challenge that lies ahead of us concerns how we can go about identifying the meanings and the forms of stance in order to be able to train a computational model to automatically identify stance in discourse. For that purpose, we need a solid theoretical ground to start from, consisting of robust criteria for detection and annotation with acceptable inter-coder reliability scores.
A comprehensive cognitive-functional framework consisting of ten notional categories for annotating stance was set up, where the basic units of analysis are utterances. The term utterance in the present study is defined as the chunk between full stops. The utterances were holistically analyzed to determine whether they expressed speaker stance or not by two expert analysts, who also identified what type s of stance were expressed in each utterance. The main principle for assigning speaker stance to an utterance was that stance-taking should be identifiable through chunks of form-meaning pairings of varying size in language, which we refer to as constructions Fillmore et al.
This procedure contrasts with a great deal of work both in quantitative corpus linguistics Biber and sentiment analysis in computational linguistics Pang and Lee , where the starting point is a preconceived list of words that the researcher assume generally express a given sentiment type. In contrast to these works, we offer an utterance-based approach to the analysis of speaker stance in communication based on the identification of constructions that actually express stance on the occasion of use.
The prospective usefulness of this study, couched in a usage-based theoretical approach to meaning in language Paradis , is automatic identification beyond mere form, i. We compiled a corpus of social media text from blogs, the Brexit Blog Corpus BBC , consisting of blog posts commenting on political issues related to the UK referendum.
BBC was annotated by two annotators, and the annotation results are evaluated and discussed. The paper is organized as follows. Section 2 presents an overview of the basic stance-taking concepts and studies in the field.
In Section 3 , the ten categories of stance are defined and exemplified. In Section 4 , the BBC is introduced.
It is described, and the annotation process and the results are presented. Section 5 evaluates the annotation results and discusses the cases of multiple stance occurrences in the corpus data. Finally, Section 6 is a summary of the findings and the implication of this study. In this section, an overview of different concepts that are used in the literature to talk about stance and studies from different academic traditions, theoretical as well as computational approaches, are considered and compared.
Speaker stance is firmly grounded in the speech situation and as such, stance-taking is crucial for the social construction of meaning in different discourses. One of the most important things we do with words is to take a stance. Stance has the power to assign value to objects of interest, to position social actors with respect to those objects, to calibrate alignment between stance takers and to invoke systems of sociocultural value.
Du Bois : Rather than providing a catalogue of stance expressions, Du Bois aims at a general understanding of the phenomenon as such. For that purpose, he finds it is necessary to pinpoint the foundational principles of taking stance and negotiating meanings Figure 1.
The stance act represented in the form of a stance triangle in Du Bois : Citation: Corpus Linguistics and Linguistic Theory ; As Figure 1 shows, evaluation, positioning and alignment are three different aspects of a single stance act, where each aspect is distinguishable from the others through the consequences it has in the act. In the stance act, the stance taker evaluates an object, thereby positions himself or herself, and aligns with other subject s.
However, to complete the picture we also add some more specifications about its nature. Even though stance as a psychological state, as in a is important for our understanding of what stance is, it is beyond the scope of this study and therefore not addressed at all.
Rather, it is considered a psychological prerequisite for this investigation. Stance-taking b and expressions of stance c , on the other hand, are both ingredients of stance constructions and important for our analysis. They are the meaning side and the form side of what we find in the utterances. Formally, stance markers are notoriously difficult to specify in advance because unlike some other categories, they are not confined to traditional areas of grammar, morphology or vocabulary, but to all of these as well as to longer chunks or even whole sentences.
The utterances in 1 — 4 below are all examples of advice of some sort, which can be expressed in a number of different ways. The use of the past tense, as with would in 1 , evokes a distancing speaker stance. The speaker stands back and makes a tentative and polite recommendation to the addressee, while the opposite holds true of the speaker stance in 2 , which is direct and therefore also much more of an urgent and potentially rude order.
In 3 , the speaker hides behind the wine. As the subject of a transitive verb in a middle construction, the wine assumes animate powers with the effect of backgrounding speaker accountability as an assessor. In addition, the use of should in the construction adds speaker tentativeness and potential uncertainty on behalf of the speaker. The active first-person construction in 4 , on the other hand, forces the speaker to stand up for his or her assessments Paradis ; Hommerberg and Paradis As our approach to stance-taking is cognitive-functional and usage-based, we are interested in how speaker stance is conveyed in real utterances.
For this reason, we explore stance from the point of view of how we interpret the meaning and the illocutionary force of the utterances in our corpus. What makes any description of stance research problematic is the fact that it is studied under a range of different names in different research traditions using different methods, and in addition to that, the sheer quantity of research is considerable.
There are many works with an explicit mention of stance in the title e. Table 1 lists a number of representative examples of work on particular types of stance. As we have already seen from the examples given above, the notion of modality is central to the notion of stance because the main contribution of items in that category is to express speaker attitude, either epistemic or deontic.
Evidentiality is related to stance-taking because it involves the mentioning of where the information given comes from, and the reliability of the source in turn relates to the marking of how reliable the information provided by the speaker is. According to the reliability hierarchy of evidentiality, information given by a speaker who saw or heard something is taken to be more trustworthy than say second-hand information reported information or when speakers draw conclusions based on clues that they obtained from elsewhere.
Thus, evidentiality is also about how the speaker obtained the information, and on the basis of that source, we infer to what extent this information can be trusted by the interlocutors. Grounding is a term mainly used in Cognitive Linguistics. It relates to the speech event, the interlocutors, the time, the place, the situational context, previous discourse and shared knowledge of the speech-act participants.
In other words, grounding is the process that links an entity or an event to the ground and thereby establishes mental contact between the event and the speech act situation. In nominal constructions, grounding is effected by determiners, demonstratives and sometimes by quantifiers, and at the clause level by markers of tense and modal verbs.
The speaker decides whether the situation described is real or potential and whether the hearer has previous knowledge of the information offered in the sentence. This is how the notion of grounding is linked to stance-taking. Subjectivity and intersubjectivity are part and parcel of all the notions and research approaches in the list above. They are broad notions with a long research tradition and have played a role in linguistics at least since Benveniste Both notions concern the human experience of being a mental agent.
Subjectivity refers the experience of oneself as a mental agent, while intersubjectivity refers the experience of others Verhagen : 4—8. Fifth, both evaluation and appraisal coincide with subjectivity and intersubjectivity in that the meanings and language resources they are related to are subjective and endorsed by the speaker, but they are also intersubjective in that they take the communicative situation and its agents into account see Hunston for an insightful comparison of evaluation, appraisal and stance, Hunston : 10— The study of stance in linguistics is mainly concerned either with theoretical approaches to different expressions of stance, i.
The starting point is typically a word or a group of words that is known to express stance. There are also studies where the goal is to explore how a notional category such as epistemic modality or degree is expressed in a given language or in different genres.
This is a research field that has grown immensely thanks to the availability of opinionated texts on the web. We expand on this in Section 2. Our take on stance in this study is broad and including. All the above notions play a role for the scope of stance that we employ for our annotations and the analysis presented in Section 3. We make use of opinionated data, like studies on opinions and sentiments. The identification of speaker stance from a computational perspective is of topical research interest in Text Mining and Computational Linguistics.
The methodologies of stance detection, stance identification and classification are grounded in similar principles, and in most cases, they are conducted using Data Mining and Machine Learning approaches, where the steps followed are concrete: data extraction and preprocessing, feature extraction, data training and testing, and evaluation of experimental results.
Stance Classification is strongly connected to the fields of Subjective Language Identification Wiebe et al. The detection of stance-taking in discourse is important for our understanding of speaker attitude, response and favorability toward a topic, an idea and a situation. In one of the early studies in the field, Whitelaw et al. They stated that more fine-grained semantic information such as the appraisal categories improves sentiment classification.
They defined linguistic clues that match an event as factual, counterfactual, not totally certain, underspecified , and created a text collection of 9, manually annotated events, the FactBank corpus. The first studies on stance detection and classification from a computational perspective used data derived from ideological online debates Somasundaran and Wiebe They created a lexicon with positive and negative entries, and showed that the sentiment- and argument-based systems outperform the baseline ones in overall accuracy Anand et al.
They used different feature sets in their approach: n-grams, cue words, post information, punctuation, etc. Furthermore, Hasan and Ng a , b , c made advances in stance classification by testing various feature sets based on syntactic dependencies and information related to the preceding post of the thread examined. Sridar et al. They showed that a content-based approach can be significantly improved when information about interactions between authors and posts are incorporated in the methodology.
Also, Faulkner set out to detect and classify stance in a different text type, namely student essays. Ferreira and Vlachos presented the Emergent data set for stance classification containing rumoured claims and 2, associated news articles.
This corpus was annotated with for, against and observing labels, and can be also used for other natural language processing NLP tasks.
Innbundet Fri frakt! Leveringstid: Sendes innen 21 dager. Om boka. Avbryt Send e-post. Les mer. Om boka Beyond Nature-Nurture: Essays in Honor of Elizabeth Bates is a very special tribute to the University of California at San Diego psycholinguist, developmental psychologist, and cognitive scientist Elizabeth Ann Bates, who died on December 14, from pancreatic cancer. Liz was a force of nature; she was also a nurturing force, as is evidenced by this collaborative collection of chapters written by many of her closest colleagues and former students.
The main aim of this paper is to analyze the relationship between brain and language in terms of coevolution. Nowadays, the thesis of coevolution is defended by the exponents of the neoculturalist paradigm to claim that language is the product of cultural not biological evolution. In our opinion, this claim is misleading. From our point of view, in fact, we can refer to the relationship between brain and language in terms of coevolution only if we are prepared to maintain that language is the product of natural selection. In our opinion, in other words, the coevolution thesis involves the idea of language as biological not cultural adaptation. Sebbene da punti di vista diversi, entrambe le critiche fanno perno sulla identificazione del linguaggio — considerato come un sistema complesso — con la grammatica universale gu. Per le ragioni che hanno portato Chomsky alla dura contrapposizione con i modelli comportamentistici e associazionistici del linguaggio, inoltre, un componente del genere deve essere innato e ricco di costituenti interni la gu risponde perfettamente ai requisiti richiesti.
Bootstrapping is a term used in language acquisition in the field of linguistics. It refers to the idea that humans are born innately equipped with a mental faculty that forms the basis of language. It is this language faculty that allows children to effortlessly acquire language. In literal terms, a bootstrap is the small strap on a boot that is used to help pull on the entire boot. Similarly in computer science , booting refers to the startup of an operation system by means of first initiating a smaller program. Therefore, bootstrapping refers to the leveraging of a small action into a more powerful and significant operation. Bootstrapping in linguistics was first introduced by Steven Pinker as a metaphor for the idea that children are innately equipped with mental processes that help initiate language acquisition.