Argumentation mining is an application of natural language processing (NLP) that emerged a few years ago and has recently enjoyed considerable popularity, as demonstrated by a series of international workshops and by a rising number of publications at the major conferences and journals of the field. Its goals are to identify argumentation in text or dialogue; to construct representations of the constellation of claims, supporting and attacking moves (in different levels of detail); and to characterize the patterns of reasoning (...) that appear to license the argumentation. Furthermore, recent work also addresses the difficult tasks of evaluating the persuasiveness and quality of arguments. Some of the linguistic genres that are being studied include legal text, student essays, political discourse and debate, newspaper editorials, scientific writing, and others. The book starts with a discussion of the linguistic perspective, characteristics of argumentative language, and their relationship to certain other notions such as subjectivity. Besides the connection to linguistics, argumentation has for a long time been a topic in Artificial Intelligence, where the focus is on devising adequate representations and reasoning formalisms that capture the properties of argumentative exchange. It is generally very difficult to connect the two realms of reasoning and text analysis, but we are convinced that it should be attempted in the long term, and therefore we also touch upon some fundamentals of reasoning approaches. Then the book turns to its focus, the computational side of mining argumentation in text. We first introduce a number of annotated corpora that have been used in the research. From the NLP perspective, argumentation mining shares subtasks with research fields such as subjectivity and sentiment analysis, semantic relation extraction, and discourse parsing. Therefore, many technical approaches are being borrowed from those (and other) fields. We break argumentation mining into a series of subtasks, starting with the preparatory steps of classifying text as argumentative (or not) and segmenting it into elementary units. Then, central steps are the automatic identification of claims, and finding statements that support or oppose the claim. For certain applications, it is also of interest to compute a full structure of an argumentative constellation of statements. Next, we discuss a few steps that try to 'dig deeper': to infer the underlying reasoning pattern for a textual argument, to reconstruct unstated premises (so-called 'enthymemes'), and to evaluate the quality of the argumentation. We also take a brief look at 'the other side' of mining, i.e., the generation or synthesis of argumentative text. The book finishes with a summary of the argumentation mining tasks, a sketch of potential applications, and a—necessarily subjective—outlook for the field. Table of Contents: Preface / Acknowledgments / Introduction / Argumentative Language / Modeling Arguments / Corpus Annotation / Finding Claims / Finding Supporting and Objecting Statements / Deriving the Structure of Argumentation / Assessing Argumentation / Generating Argumentative Text / Summary and Perspectives / Bibliography / Authors' Biographies / Index. (shrink)

Argumentation mining aims to automatically detect, classify and structure argumentation in text. Therefore, argumentation mining is an important part of a complete argumentation analyisis, i.e. understanding the content of serial arguments, their linguistic structure, the relationship between the preceding and following arguments, recognizing the underlying conceptual beliefs, and understanding within the comprehensive coherence of the specific topic. We present different methods to aid argumentation mining, starting with plain argumentation detection and moving forward to a more structural analysis (...) of the detected argumentation. Different state-of-the-art techniques on machine learning and context free grammars are applied to solve the challenges of argumentation mining. We also highlight fundamental questions found during our research and analyse different issues for future research on argumentation mining. (shrink)

Argumentation mining is an advanced form of human language understanding by the machine. This is a challenging task for a machine. When sufficient explicit discourse markers are present in the lang...

The generalised, automated reconstruction of the reasoning structures underlying persuasive communication is an enormously challenging task. While this work in argument mining is increasingly informed by the rich tradition of argumentation studies outside the computational field, the rhetorical perspective on argumentation is thus far largely ignored. To explore the application of rhetorical insights in argument mining, we conduct a pilot study on the connection between rhetorical figures and argumentation structure. Rhetorical figures are linguistic devices that perform (...) a variety of functions in argumentative discourse. The textual form of some of these figures is easy to identify automatically, such that an established connection between the figure and a preponderance of argumentative content would improve the performance of argument mining techniques. Furthermore, the automated mining of rhetorical figures could be used as an empirical, corpus-based testing ground for the claims made about these figures in the rhetorical literature. In the pilot study, we explore the connection between eight rhetorical figures the forms of which we expect to be relatively easy to identify computationally, and argumentation structure (concretely, we consider the six schemes ‘anadiplosis’, ‘epanaphora’, ‘epistrophe’, ‘epizeuxis’, ‘eutrepismus’, and ‘polyptoton’, and the two tropes ‘antithesis’ and ‘dirimens copulatio’, and relate their occurrences to relations of inference and conflict). The data of the study is collected in the MM2012c corpus of 39,694 words of argumentatively annotated transcripts from the BBC Radio 4’s Moral Maze discussion program. We show that some of the figures indeed correspond to passages of high argumentative density, relative to the text as a whole. (shrink)

Given a controversial issue, argument mining from texts in natural language is extremely challenging: besides linguistic aspects, domain knowledge is often required together with appropriate forms of inferences to identify arguments. Via the analysis of various corpora, this contribution explores the types of knowledge that are required to develop an efficient argument mining system. We show that the Qualia structure of the Generative Lexicon with some extensions and a specific interpretation has some expressive capabilities which are (...) appropriate for this task. (shrink)

The generalised, automated reconstruction of the reasoning structures underlying persuasive communication is an enormously challenging task. While this work in argument mining is increasingly informed by the rich tradition of argumentation studies outside the computational field, the rhetorical perspective on argumentation is thus far largely ignored. To explore the application of rhetorical insights in argument mining, we conduct a pilot study on the connection between rhetorical figures and argumentation structure. Rhetorical figures are linguistic devices that perform (...) a variety of functions in argumentative discourse. The textual form of some of these figures is easy to identify automatically, such that an established connection between the figure and a preponderance of argumentative content would improve the performance of argument mining techniques. Furthermore, the automated mining of rhetorical figures could be used as an empirical, corpus-based testing ground for the claims made about these figures in the rhetorical literature. In the pilot study, we explore the connection between eight rhetorical figures the forms of which we expect to be relatively easy to identify computationally, and argumentation structure (concretely, we consider the six schemes ‘anadiplosis’, ‘epanaphora’, ‘epistrophe’, ‘epizeuxis’, ‘eutrepismus’, and ‘polyptoton’, and the two tropes ‘antithesis’ and ‘dirimens copulatio’, and relate their occurrences to relations of inference and conflict). The data of the study is collected in the MM2012c corpus of 39,694 words of argumentatively annotated transcripts from the BBC Radio 4’s Moral Maze discussion program. We show that some of the figures indeed correspond to passages of high argumentative density, relative to the text as a whole. (shrink)

Abstract“Natural syllogisms” are arguments formally identifiable with categorical syllogisms that have an implicit universal affirmative premise retrieved from semantic memory rather than explicitly stated. Previous studies with adult participants (Politzer, 2011) have shown that the rate of success is remarkably high. Because their resolution requires only the use of a simple strategy (known as ecthesis in classic logic) and an operational use of the concept of inclusion (the recognition that an element that belongs to a subset must belong to the (...) set but not vice versa), it was hypothesized that these syllogisms would be within the grasp of non‐adult participants, provided they have acquired the notion of deductive validity. Here, 11‐year‐old children were presented with natural syllogisms embedded in short dialogs. The first experiment showed that their performance was equivalent to adults' highest level of performance in standard experiments on syllogisms. The second experiment, while confirming children's proficiency in solving natural syllogisms, showed that they outperformed children who solved non‐natural matched syllogisms in the same experimental setting. The results are also in agreement with the argumentation theory of reasoning. (shrink)

Available corpora for Argument Mining differ along several axes, and one of the key differences is the presence (or absence) of discourse markers to signal argumentative content. Exploring effective ways to use discourse markers has received wide attention in various discourse parsing tasks, from which it is well-known that discourse markers are strong indicators of discourse relations. To improve the robustness of Argument Mining systems across different genres, we propose to automatically augment a given text with (...) discourse markers such that all relations are explicitly signaled. Our analysis unveils that popular language models taken out-of-the-box fail on this task; however, when fine-tuned on a new heterogeneous dataset that we construct (including synthetic and real examples), they perform considerably better. We demonstrate the impact of our approach on an Argument Mining downstream task, evaluated on different corpora, showing that language models can be trained to automatically fill in discourse markers across different corpora, improving the performance of a downstream model in some, but not all, cases. Our proposed approach can further be employed as an assistant tool for better discourse understanding. (shrink)

Growth of the private sector and privatization of state companies around the world have led to the emergence of various stock markets, some of which are depicted by insider trading. Law literature uses the arguments of unfairness, breach of fiduciary rights and damage to others to define and rule against insider trading. Economic literature can be used to interpret insider trading from other perspectives. This study argues that the question of insider trading in developing markets can be resolved by the (...) extent stock markets generate externalities and are public goods. It advocates structural changes in the developing markets and examines the conditions under which the Coase Theorem would work. (shrink)

This paper surveys ontological modeling of rhetorical concepts, developed for use in argument mining and other applications of computational rhetoric, projecting their future directions. We include ontological models of argument schemes applying Rhetorical Structure Theory (RST); the RhetFig proposal for modeling; the related RetFig Ontology of Rhetorical Figures for Serbian (developed by two of the authors); and the Lassoing Rhetoric project (developed by another of the authors). The Lassoing Rhetoric venture is interesting for its multifaceted approach to (...) linguistic devices, prominently including rhetorical figures, but also RST relations and stylistic models, like the use of historic present. This application takes a natural language text input and uses syntactic parsing tools to produce a knowledge base of linguistic entities using references to an OWL ontological framework, locating these devices using Semantic Web Rule Language (SWRL) logic rules. The paper also reports on a similar approach in research into detecting ironic tweets in a Serbian twitter corpus. The rhetorical schemes used for argument mining are also presented, as well as some suggestions for novel argument schemes based on the ontological approach to rhetorical figuration. (shrink)

This paper surveys ontological modeling of rhetorical concepts, developed for use in argument mining and other applications of computational rhetoric, projecting their future directions. We include ontological models of argument schemes applying Rhetorical Structure Theory (RST); the RhetFig proposal for modeling; the related RetFig Ontology of Rhetorical Figures for Serbian (developed by two of the authors); and the Lassoing Rhetoric project (developed by another of the authors). The Lassoing Rhetoric venture is interesting for its multifaceted approach to (...) linguistic devices, prominently including rhetorical figures, but also RST relations and stylistic models, like the use of historic present. This application takes a natural language text input and uses syntactic parsing tools to produce a knowledge base of linguistic entities using references to an OWL ontological framework, locating these devices using Semantic Web Rule Language (SWRL) logic rules. The paper also reports on a similar approach in research into detecting ironic tweets in a Serbian twitter corpus. The rhetorical schemes used for argument mining are also presented, as well as some suggestions for novel argument schemes based on the ontological approach to rhetorical figuration. (shrink)

The dominant approach to argument mining has been to treat it as a machine learning problem based upon superficial text features, and to treat the relationships between arguments as either support...

A macroscope is proposed and tested here for the discovery of the unique argumentative footprint that characterizes how a collective manages differences and pursues disagreement through argument in a polylogue. The macroscope addresses broader analytic problems posed by various conceptualizations of large-scale argument, such as fields, spheres, communities, and institutions. The design incorporates a two-tier methodology for detecting argument patterns of the arguments performed in arguing by an interactive collective that produces views, or topographies, of the ways (...) that issues are generated in the making and defending of standpoints. The design premises for the macroscope build on insights about argument patterns from pragma-dialectical theory by incorporating research and theory on disagreement management and the Argumentum Model of Topics. The design reconceptualizes prototypical and stereotypical argument patterns for characterizing large-scale argumentation. A prototype of the macroscope is tested on data drawn from six threads about oil-drilling and fracking from the subreddit Changemyview. The implementation suggests the efficacy of the macroscope’s design and potential for identifying what communities make controversial and how the disagreement space in a polylogue is managed through stereotypical argument patterns in terms of claims/premises, inferential relations, and presentational devices. (shrink)

Identifying, classifying, and analyzing arguments in legal discourse has been a prominent area of research since the inception of the argument mining field. However, there has been a major discrepancy between the way natural language processing (NLP) researchers model and annotate arguments in court decisions and the way legal experts understand and analyze legal argumentation. While computational approaches typically simplify arguments into generic premises and claims, arguments in legal research usually exhibit a rich typology that is important for (...) gaining insights into the particular case and applications of law in general. We address this problem and make several substantial contributions to move the field forward. First, we design a new annotation scheme for legal arguments in proceedings of the European Court of Human Rights (ECHR) that is deeply rooted in the theory and practice of legal argumentation research. Second, we compile and annotate a large corpus of 373 court decisions (2.3M tokens and 15k annotated argument spans). Finally, we train an argument mining model that outperforms state-of-the-art models in the legal NLP domain and provide a thorough expert-based evaluation. All datasets and source codes are available under open lincenses athttps://github.com/trusthlt/mining-legal-arguments. (shrink)

In this paper we look at the manual analysis of arguments and how this compares to the current state of automatic argument analysis. These considerations are used to develop a new approach combining a machine learning algorithm to extract propositions from text, with a topic model to determine argument structure. The results of this method are compared to a manual analysis.

Interaction mining is about discovering and extracting insightful information from digital conversations, namely those human–human information exchanges mediated by digital network technology. We present in this article a computational model of natural arguments and its implementation for the automatic argumentative analysis of digital conversations, which allows us to produce relevant information to build interaction business analytics applications overcoming the limitations of standard text mining and information retrieval technology. Applications include advanced visualisations and abstractive summaries.

When you have a conscious experience—such as feeling pain, watching the sunset, or thinking about your loved ones—are you aware of the experience as your own, even when you do not reflect on, think about, or attend to it? Let us say that an experience has “mineness” just in case its subject is aware of it as her own while she undergoes it. And let us call the view that all ordinary experiences have mineness “typicalism.” Recently, Guillot has offered a (...) novel argument for typicalism by leveraging the relation between self-knowledge and self-awareness. She starts by arguing that all ordinary experiences give their subjects immediate justification to believe that their experiences are their own. She then argues that this can be explained by typicalism. In this paper, I argue that her argument fails. I start by clarifying the notion of mineness and giving more details about her argument. I then explain why her argument fails by raising doubts about whether typicalism explains the target explanandum. I close by considering some implications of our discussion for self-knowledge. (shrink)

Recently, there has been a heavy debate in the US about the government’s use of data mining in its fight against terrorism. Privacy concerns in fact led the Congress to terminate the funding of TIA, a program for advanced information technology to be used in the combat of terrorism. The arguments put forward in this debate, more specifically those found in the main report and minority report by the TAPAC established by the Secretary of Defense to examine the TIA (...) issue, will be analysed to trace the deeper roots of this controversy. This analysis will in turn be used as a test case to examine the adequacy of the usual theoretical frameworks for these kinds of issues, in particular the notion of privacy. Whereas the dominant theoretical framing of the notion of privacy turns around access to information, most of the core arguments in the debate do not fit in this kind of framework. The basic disagreements in the controversy are not about mere access, they involve both access and use. Furthermore, whereas the issue of access by itself refers to a more or less static situation, the real disagreements much more concern the organisational dynamics of the use of information, the mechanisms in the organisation that control these dynamics, and the awareness present within the organisation of the ‘social risks’ these dynamics represent. The bottom line question is whether the assessment of these gives sufficient reason for trust. (shrink)

In recent debates on phenomenal consciousness, a distinction is sometimes made, after Levine (2001) and Kriegel (2009), between the “qualitative character” of an experience, i.e. the specific way it feels to the subject (e.g. blueish or sweetish or pleasant), and its “subjective character”, i.e. the fact that there is anything at all that it feels like to her. I argue that much discussion of subjective character is affected by a conflation between three different notions. I start by disentangling the three (...) notions in question, under the labels of “for-me-ness”, “me-ness” and “mineness”. Next, I argue that these notions are not equivalent; in particular, there is no conceptual implication from for-me-ness to me-ishness or mineness. Empirical considerations based on clinical cases additionally suggest that the three notions may also correspond to different properties (although the claim of conceptual non-equivalence does not depend on this further point). The aim is clarificatory, cautionary but also critical: I examine four existing arguments from subjective character that are fuelled by an undifferentiated use of the three notions, and find them to be flawed for this reason. (shrink)

A famous theorem by van der Waerden states the following: Given any finite coloring of the integers, one color contains arbitrarily long arithmetic progressions. Equivalently, for every q,k, there is an N = N(q,k) such that for every q-coloring of an interval of length N one color contains a progression of length k. An obvious question is what is the growth rate of N = N(q,k). Some proofs, like van der Waerden's combinatorial argument, answer this question directly, while the (...) topological proof by Furstenberg and Weiss does not. We present an analysis of (Girard's variant of) Furstenberg and Weiss's proof based on monotone functional interpretation, both yielding bounds and providing a general illustration of proof mining in topological dynamics. The bounds do not improve previous results by Girard, but only—as is also revealed by the analysis—because the combinatorial proof and the topological dynamics proof in principle are identical. (shrink)

By resituating Alexander von Humboldt in the “working world” of mining, this essay offers a case study of the way in which industry has shaped practice and theory in the history of science. While Humboldt’s experience as a miner in Saxony and Prussia provided him a venue in which to study fossilized vegetation, revealing a fundamental link between the migrations of plants and of peoples, industrial concerns about miners’ safety inspired a study of the interplay between plants and people (...) that shaped his later articulation of the verticality of plant distribution. Moreover, the cartographic methods Humboldt employed during his American journey depended as much on drawing practices indebted to mining as they did on patterns of vertical mobility above and below the surface of the earth. These arguments ultimately encourage a departure from “Humboldtian Science,” a term that has veiled an originally Prusso-Saxon science beneath a set of Anglo-American connotations. (shrink)

It’s a familiar fact that there is something it is like to see red, eat chocolate or feel pain. More recently philosophers have insisted that in addition to this objectual phenomenology there is something it is like for me to eat chocolate, and this for-me-ness is no less there than the chocolatishness. Recognizing this subjective feature of consciousness helps shape certain theories of consciousness, introspection and the self. Though it does this heavy philosophical work, and it is supposed to be (...) relatively obvious to anyone who introspects, it is rather difficult to see just what this phenomenal me-ness is supposed to be; indeed, many philosophers deny it exists. In this paper we try to provide a clear sense of what phenomenal me-ness involves, and then then consider some arguments for the existence of phenomenal me-ness experience as well as some accounts of what gives rise to it. In the end, we argue that the plausible senses of me-ness are a good deal thinner than what often seems to be claimed. (shrink)

Traditional document clustering algorithms consider text-based features such as unique word count, concept count, etc. to cluster documents. Meanwhile, event mining is the extraction of specific events, their related sub-events, and the associated semantic relations from documents. This work discusses an approach to event mining through clustering. The Universal Networking Language -based subgraph, a semantic representation of the document, is used as the input for clustering. Our research focuses on exploring the use of three different feature sets for (...) event clustering and comparing the approaches used for specific event mining. In our previous work, the clustering algorithm used UNL-based event semantics to represent event context for clustering. However, this approach resulted in different events with similar semantics being clustered together. Hence, instead of considering only UNL event semantics, we considered assigning additional weights to similarity between event contexts with event-related attributes such as time, place, and persons. Although we get specific events in a single cluster, sub-events related to the specific events are not necessarily in a single cluster. Therefore, to improve our cluster efficiency, connective terms between two sentences and their representation as UNL subgraphs were also considered for similarity determination. By combining UNL semantics, event-specific arguments similarity, and connective term concepts between sentences, we were able to obtain clusters for specific events and their sub-events. We have used 112 000 Tamil documents from the Forum for Information Retrieval Evaluation data corpus and achieved good results. We have also compared our approach with the previous state-of-the-art approach for Router-RCV1 corpus and achieved 30% improvements in precision. (shrink)

The claim that phenomenal consciousness essentially involves self-consciousness, in the sense of _mineness_, has gained momentum in recent years. In this paper, I discuss the main non-phenomenological, theoretical argument for this claim: the so-called “transcendental argument” for universal mineness (Zahavi 2018, p. 711), which, in essence, corresponds to Shoemaker’s critique of the perceptual model of self-consciousness. I point out the potential of the transcendental argument, but most importantly its limitations. And I show that, even if successful, the (...) argument cannot vindicate the claim of an essential connection between phenomenal consciousness and self-consciousness. Since the transcendental argument is depicted as the “central argument” for universal mineness (Zahavi 2018, p. 711), I contend that, in view of its failure, the claim that all of my experiences have to be given to me _as mine_, all of your experiences have to be given to you _as yours_, etc., appears insufficiently substantiated. The idea that there is an essential connection between phenomenal consciousness and self-consciousness must be called into question. (shrink)

This study examines the ethical position and behaviour of multinational mining companies regarding hazardous employment and health and safety of employees in the South African mining industry. Mining companies have long had a reputation for being unethical on health and safety issues. Too often there are occurrences of fatal accidents, which bring the ethical behaviour of multinational mining companies into question. The litmus test for the mining companies is to devise benchmark standards that will reduce (...) accidents tremendously at their place of operations. This study addresses this issue by examining measures and regulations set up to check the occurrences of mining accidents in South Africa. It follows that the remedy needs to be fundamental and thoroughgoing. (shrink)

Many philosophers hold that phenomenally conscious experiences involve a sense of mineness, since experiences like pain or hunger are immediately presented as mine. What can be said about this mineness, and does acceptance of this feature commit us to the existence of a subject or self? If yes, how should we characterize this subject? This paper considers the possibility that, to the extent that we accept this feature, it provides us with a minimal notion of a subject of experience, and (...) that the phenomenological subject of experience, as it is represented in conscious experience, is the organism. While many philosophers agree that the metaphysical subject of experience is the animal, this claim is much less widespread, maybe even counterintuitive. The argument for this claim alludes to the structure of phenomenal consciousness and to recent work in cognitive science concerning the embodied character of consciousness and cognition. To illustrate the problems of current controversies, not only several recent rejections of a subject of experience are critically discussed, but also Hume’s famous rejection of a subject is criticized making use of epistemological aspects from Kant’s philosophy of mind. The final section situates the present discussion in the context of recently popular predictive coding accounts of perception and perceptual experience. (shrink)

We appreciate the opportunity to present some further thoughts on the libertarian right to test initially proposed by Loi, and hope these additional comments will further inform debate about this critical emerging technology. Loi’s important argument is that individuals possess a prima facie libertarian right to test their genomes and that regulatory intervention restricting genetic testing must be justified by those proposing regulation. Our position is that the onus of justifying regulation is reversed. The risk to others whose genomic (...) information is shared with the individual is potentially significant enough to warrant prima facie regulatory intervention, including protection against misuse of genetic information derived from those tests, not just against the individual tested but also against those who for reasons of common familial ancestry are also susceptible to misuse. Testing an individual’s genome does not merely reveal information about that individual; it reveals, or renders reasonably inferable, information about the genomes of close relatives due to the commonality of genomic DNA within families. Such commonality is not merely ‘incidentally identical’: it is instead inevitable given the shared nature of genomic DNA sequences within families. ‘Incidental identity’ may appropriately describe the statistical possibility of two unrelated individuals in the human …. (shrink)

"Data mining is not an invasion of privacy because access to data is only by machines, not by people": this is the argument that is investigated here. The current importance of this problem is developed in a case study of data mining in the USA for counterterrorism and other surveillance purposes. After a clarification of the relevant nature of privacy, it is argued that access by machines cannot warrant the access to further information, since the analysis will (...) have to be made either by humans or by machines that understand. It concludes that the current data mining violates the right to privacy and should be subject to the standard legal constraints for access to private information by people. (shrink)

Extremism has been a problematic term to define and suggests different and opposing meanings. This study explores how Twitter users conceptualize extremism in Arabic and express their opinions/arguments to construct the term. A corpus of tweets was collected from Twitter API using the word ‘تطرف أو متطرف’ in Arabic for extremist/extremism. A topic modeling algorithm was then applied to the dataset to uncover latent associated concepts underlying extremism, followed by a critical discourse analysis using Van Dijk’s Sociocognitive approach. The discursive (...) and linguistic strategies used by Twitter users to support and justify their views of extremism were examined. The findings demonstrate an ideological influence that controls the concept of extremism, keeping it open to manipulation to serve shared interests and goals. Arab users of Twitter use extremism to promote their groups’ positive schema against others-negative schema. (shrink)

:This article examines privacy threats arising from the use of data mining by private Australian health insurance companies. Qualitative interviews were conducted with key experts, and Australian governmental and nongovernmental websites relevant to private health insurance were searched. Using Rationale, a critical thinking tool, the themes and considerations elicited through this empirical approach were developed into an argument about the use of data mining by private health insurance companies. The argument is followed by an ethical analysis (...) guided by classical philosophical theories—utilitarianism, Mill’s harm principle, Kant’s deontological theory, and Helen Nissenbaum’s contextual integrity framework. Both the argument and the ethical analysis find the use of data mining by private health insurance companies in Australia to be unethical. Although private health insurance companies in Australia cannot use data mining for risk rating to cherry-pick customers and cannot use customers’ personal information for unintended purposes, this article nonetheless concludes that the secondary use of customers’ personal information and the absence of customers’ consent still suggest that the use of data mining by private health insurance companies is wrong. (shrink)

An important factor of argument mining in dialog or multilog data is the framing with which interlocutors put forth their arguments. By using rhetorical devices such as hedging or reference to the Common Ground, speakers relate themselves to their interlocutors, their arguments, and the ongoing discourse. Capitalizing on theoretical linguistic insights into the semantics and pragmatics of discourse particles in German, we propose a categorization of rhetorical information that is highly relevant in natural transcribed speech. In order to (...) shed light on the rhetorical strategies of different interlocutors in large amounts of real mediation data, we use a method from Visual Analytics which allows for an exploration of the rhetorical patterns via an interactive visual interface. With this innovative combination of theoretical linguistics, argument mining and information visualization, we offer a novel way of analyzing framing strategies in large amounts of multi-party argumentative discourse in German. (shrink)

This paper examines the issue of acid mine drainage in South Africa and environmental decision making processes that could be taken to mitigate the problem in the context of both conventional risk assessment and the precautionary principle. It is argued that conventional risk assessment protects the status quo and hence cannot be entirely relied upon as an effective tool to resolve environmental problems in the context of South Africa, a developing country with complex environmental health concerns. The complexity of the (...) environmental issues is discussed from historical and political perspectives. An argument is subsequently made that the precautionary principle is an alternative tool, and its adoption can be used to empower local communities. This work, therefore, adds to new knowledge by problematising conventional risk assessment and proposing the framing of the acid mine drainage issues in a complex and contextual scenario of a developing country—South Africa. (shrink)

An important factor of argument mining in dialog or multilog data is the framing with which interlocutors put forth their arguments. By using rhetorical devices such as hedging or reference to the Common Ground, speakers relate themselves to their interlocutors, their arguments, and the ongoing discourse. Capitalizing on theoretical linguistic insights into the semantics and pragmatics of discourse particles in German, we propose a categorization of rhetorical information that is highly relevant in natural transcribed speech. In order to (...) shed light on the rhetorical strategies of different interlocutors in large amounts of real mediation data, we use a method from Visual Analytics which allows for an exploration of the rhetorical patterns via an interactive visual interface. With this innovative combination of theoretical linguistics, argument mining and information visualization, we offer a novel way of analyzing framing strategies in large amounts of multi-party argumentative discourse in German. (shrink)

This paper explains the importance of classifying argumentation schemes, and outlines how schemes are being used in current research in artificial intelligence and computational linguistics on argument mining. It provides a survey of the literature on scheme classification. What are so far generally taken to represent a set of the most widely useful defeasible argumentation schemes are surveyed and explained systematically, including some that are difficult to classify. A new classification system covering these centrally important schemes is built.

Using a Rawlsian approach to analyze the ethical implications of data mining within three major codes of ethics used by American marketing firms, the author argues that marketers should re-conceptualize their business conduct, as defined in their individual codes of ethics, to incorporate a Rawlsian concern for society's least advantaged members. Rawls's concept of primary goods provides the framework for the argument that anonymity, a component of privacy, is vital for consumers whose autonomy is affected by data (...) class='Hi'>mining. A combination of practical measures, ethical guidelines, and legislative protections are recommended for minimizing concerns about data mining, while still allowing for commercial advantages provided by the practice. (shrink)

In this paper, it is argued that although data mining (DM) is being touted as a solution to many business problems and is basking in the glory of electronic business environments of today, as practiced currently, it reflects a preoccupation with short-run commercial applications and a neglect of the underlying theoretical issues. Although an argument can be made that theoretical precedence is not a necessary prerequisite for practical application or for commercial success, it can also be argued that (...) an exclusive reliance on data-driven and exploratory components of pattern recognition without a corresponding attention to the causal schemas underlying patterns is destined to limit the potential for DM to evolve into a long-term solution to business problems or into an intellectual discipline in its own right. This paper presents an overview of key features and assumptions in DM and examines some of the key practical, philosophical, and foundational issues in DM. (shrink)

Argumentation schemes have played a key role in our research projects on computational models of natural argument over the last decade. The catalogue of schemes in Walton, Reed and Macagno’s 2008 book, Argumentation Schemes, served as our starting point for analysis of the naturally occurring arguments in written text, i.e., text in different genres having different types of author, audience, and subject domain (genetics, international relations, environmental science policy, AI ethics), for different argument goals, and for different possible (...) future applications. We would often first attempt to analyze the arguments in our corpora in terms of those schemes, then adapt schemes as needed for the goals of the project, and in some cases implement them for use in computational models. Among computational researchers, the main interest in argumentation schemes has been for use in argument mining by applying machine learning methods to existing argument corpora. In contrast, a primary goal of our research has been to learn more about written arguments themselves in various contemporary fields. Our approach has been to manually analyze semantics, discourse structure, argumentation, and rhetoric in texts. Another goal has been to create sharable digital corpora containing the results of our studies. Our approach has been to define argument schemes for use by human corpus annotators or for use in logic programs for argument mining. The third goal is to design useful computer applications based upon our studies, such as argument diagramming systems that provide argument schemes as building blocks. This paper describes each of the various projects: the methods, the argument schemes that were identified, and how they were used. Then a synthesis of the results is given with a discussion of open issues. (shrink)

Argumentation schemes have played a key role in our research projects on computational models of natural argument over the last decade. The catalogue of schemes in Walton, Reed and Macagno’s 2008 book, Argumentation Schemes, served as our starting point for analysis of the naturally occurring arguments in written text, i.e., text in different genres having different types of author, audience, and subject domain, for different argument goals, and for different possible future applications. We would often first attempt to (...) analyze the arguments in our corpora in terms of those schemes, then adapt schemes as needed for the goals of the project, and in some cases implement them for use in computational models. Among computational researchers, the main interest in argumentation schemes has been for use in argument mining by applying machine learning methods to existing argument corpora. In contrast, a primary goal of our research has been to learn more about written arguments themselves in various contemporary fields. Our approach has been to manually analyze semantics, discourse structure, argumentation, and rhetoric in texts. Another goal has been to create sharable digital corpora containing the results of our studies. Our approach has been to define argument schemes for use by human corpus annotators or for use in logic programs for argument mining. The third goal is to design useful computer applications based upon our studies, such as argument diagramming systems that provide argument schemes as building blocks. This paper describes each of the various projects: the methods, the argument schemes that were identified, and how they were used. Then a synthesis of the results is given with a discussion of open issues. (shrink)

In response to an accusation of having said something inappropriate, the accused may exploit the difference between the explicit contents of their utterance and its implicatures. Widely discussed in the pragmatics literature are those cases in which arguers accept accountability only for the explicit contents of what they said while denying commitment to the implicature. In this paper, we sketch a fuller picture of commitment denial. We do so, first, by including in our discussion not just denial of implicatures, but (...) also the mirror strategy of denying commitment to literal meaning and, second, by classifying strategies for commitment denial in terms of classical rhetorical status theory. In addition to providing a systematic categorization of our data, this approach offers some clues to determine when such a defence strategy is a reasonable one and when it is not. (shrink)

In this article I address the ethical implications of the legal issues the U. S. Supreme Court resolved in New York Times v. Sullivan and its progeny. In a ruling with far-reaching moral implications, the Court addressed truthtelling-journalism's primary ethical directive-and undermined it by favoring other moral principles and social goals. Much of this article focuses on the ethical arguments addressed to the Court in legal briefs that sought rulings that would support fundamental principals of ethical journalism. The creation of (...) actual malice as a legal concept in the Sullivan case owes more to the Court's pursuit of other moral and social values than strict legal reasoning, according to the descriptive theory of pragmatic instrumentalism, which informs this analysis. (shrink)

There is a driving need computationally to interrogate large bodies of text for a range of non-denotative meaning (e.g., to plot chains of reasoning, detect sentiment, diagnose genre, and so forth). But such meaning has always proven computationally allusive. It is often implicit, ‘hidden’ meaning, evoked by linguistic cues, stylistic arrangement, or conceptual structure – features that have hitherto been difficult for Natural Language Processing systems to recognize and use. Non-denotative textual effects are the historical concern of rhetorical studies, and (...) we have turned to rhetoric in order to find new ways to advance NLP, especially for sophisticated tasks like Argument Mining. This paper highlights certain rhetorical devices that encode levels of meaning that have been overlooked in Computational Linguistics generally and Argument Mining particularly, and yet lend themselves to automated detection. These devices are the linguistic configurations known as Rhetorical Figures. We argue for the importance of these devices for Argument Mining, especially in collocations, and we present an XML annotation scheme for Rhetorical Figures to make figuration more tractable for computational approaches, particularly with an eye on the improvements they offer Argument Mining. We also discuss the intellectual and technical challenges involved in figure annotation and the implications for Machine Learning. (shrink)

Argumentation schemes can be described as abstract structures representing the most generic types of argument, constituting the building blocks of the ones used in everyday reasoning. This paper investigates the structure, classification, and uses of such schemes. Three goals are pursued: 1) to describe the schemes, showing how they evolved and how they have been classified in the traditional and the modern theories; 2) to propose a method for classifying them based on ancient and modern developments; and 3) to (...) outline and show how schemes can be used to describe and analyze or produce real arguments. To this purpose, we will build on the traditional distinctions for building a dichotomic classification of schemes, and we will advance a modular approach to argument analysis, in which different argumentation schemes are combined together in order to represent each step of reasoning on which a complex argument relies. Finally, we will show how schemes are applied to formal systems, focusing on their applications to Artificial Intelligence, AI & Law, argument mining, and formal ontologies. (shrink)

There is a driving need computationally to interrogate large bodies of text for a range of non-denotative meaning (e.g., to plot chains of reasoning, detect sentiment, diagnose genre, and so forth). But such meaning has always proven computationally allusive. It is often implicit, ‘hidden’ meaning, evoked by linguistic cues, stylistic arrangement, or conceptual structure – features that have hitherto been difficult for Natural Language Processing systems to recognize and use. Non-denotative textual effects are the historical concern of rhetorical studies, and (...) we have turned to rhetoric in order to find new ways to advance NLP, especially for sophisticated tasks like Argument Mining. This paper highlights certain rhetorical devices that encode levels of meaning that have been overlooked in Computational Linguistics generally and Argument Mining particularly, and yet lend themselves to automated detection. These devices are the linguistic configurations known as Rhetorical Figures. We argue for the importance of these devices for Argument Mining, especially in collocations, and we present an XML annotation scheme for Rhetorical Figures to make figuration more tractable for computational approaches, particularly with an eye on the improvements they offer Argument Mining. We also discuss the intellectual and technical challenges involved in figure annotation and the implications for Machine Learning. (shrink)

Identifying rhetorical figures with marginal to non-existent lexico-syntactic signatures poses significant challenges for computational approaches reliant upon structural definitions or descriptions. One such figure is prolepsis ([Formula: see text]ó[Formula: see text]), which this essay charts out in some detail, addressing the challenges and the benefits of rendering such figures computationally tractable through the use of argument schemes with attention to metadiscursive or macro-discursive norms offered by pragma-dialectical traditions.

This paper explains the importance of classifying argumentation schemes, and outlines how schemes are being used in current research in artificial intelligence and computational linguistics on argument mining. It provides a survey of the literature on scheme classification. What are so far generally taken to represent a set of the most widely useful defeasible argumentation schemes are surveyed and explained systematically, including some that are difficult to classify. A new classification system covering these centrally important schemes is built.

Identifying rhetorical figures with marginal to non-existent lexico-syntactic signatures poses significant challenges for computational approaches reliant upon structural definitions or descriptions. One such figure is prolepsis ([Formula: see text]ó[Formula: see text]), which this essay charts out in some detail, addressing the challenges and the benefits of rendering such figures computationally tractable through the use of argument schemes with attention to metadiscursive or macro-discursive norms offered by pragma-dialectical traditions.

This work investigates the role of semantic clause types and modality in argumentative texts. We annotate argumentative microtexts with situation entity (SE) classes and additionally label the segments that contain modal verbs with their modal senses. We analyse the correlation both of SE classes and of modal verbs and senses with components of argument structures (such as premises and conclusions) and their functions (such as support and rebuttal). We find interesting tendencies in the correlations between both argument components (...) and argumentative functions with SE types. We also see interesting differences in the distributions of modal verbs and senses within different argumentative components and functions, as well as evidence that modal senses can be helpful to distinguish conclusions and premises. We conclude that both semantic clause types and modal senses can be deployed for automatic recognition and fine-grained classification of argumentative text passages. (shrink)