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Unlike traditional text corpora collected from trustworthy sources, the content of web based corpora has to be filtered. This study briefly discusses the impact of web spam on corpus usability and emphasizes the importance of removing computer generated text from web corpora.
The paper also presents a keyword comparison of an unfiltered corpus with the same collection of texts cleaned by a supervised classifier trained using FastText. The classifier was able to recognize 71% of web spam documents similar to the training set but lacked both precision and recall when applied to short texts from another data set.
This study investigates the interrelations between bilingual development (German/Russian), immigration and integration in the host society. Participants are Russian-Germans, that is, ethnic Germans who have repatriated to Germany from the former Soviet Union. They were part of a longitudinal study dedicated to the integration of multi-generation Russian-German families in Germany. The paper focuses on eight Russian-Germans who moved to Germany between the ages of five and eight and are now young adults. The analysis is based on interviews conducted in the twentieth year of their life in Germany in German and Russian, A semi-structured questionnaire was used to elicit information on the main stages of integration, the use of the languages, the attitudes towards German and Russian, and an assessment of the current situation. The obtained data were used to make an initial assessment of the oral language competencies of the participants and as sources of information about the objective facts and subjective attitudes that determined linguistic and social integration.
Corpus researchers, along with many other disciplines in science are being put under continual pressure to show accountability and reproducibility in their work. This is unsurprisingly difficult when the researcher is faced with a wide array of methods and tools through which to do their work; simply tracking the operations done can be problematic, especially when toolchains are often configured by the developers, but left largely as a black box to the user. Here we present a scheme for encoding this ‘meta data’ inside the corpus files themselves in a structured data format, along with a proof-of-concept tool to record the operations performed on a file.
This article describes a series of ongoing efforts at the Stanford Literary Lab to manage a large collection of literary corpora (~40 billion words). This work is marked by a tension between two competing requirements – the corpora need to be merged together into higher-order collections that can be analyzed as units; but, at the same time, it’s also necessary to preserve granular access to the original metadata and relational organization of each individual corpus. We describe a set of data management practices that try to accommodate both of these requirements – Apache Spark is used to index data as Parquet tables on an HPC cluster at Stanford. Crucially, the approach distinguishes between what we call “canonical” and “combined” corpora, a variation on the well-established notion of a “virtual corpus” (Kupietz et al., 2014; Jakubíek et al., 2014; van Uytvanck, 2010).
Our paper describes an experiment aimed to assessment of lexical coverage in web corpora in comparison with the traditional ones for two closely related Slavic languages from the lexicographers’ perspective. The preliminary results show that web corpora should not be considered ― inferior, but rather ― different.
The Manatee corpus management system on which the Sketch Engine is built is efficient, but unable to harness the power of today’s multiprocessor machines. We describe a new, compatible implementation of Manatee which we develop in the Go language and report on the performance gains that we obtained.
Creating CorCenCC (Corpws Cenedlaethol Cymraeg Cyfoes - The National Corpus of Contemporary Welsh)
(2017)
CorCenCC is an interdisciplinary and multiinstitutional project that is creating a large-scale, open-source corpus of contemporary Welsh. CorCenCC will be the first ever large-scale corpus to represent spoken, written and electronicallymediated Welsh (compiling an initial data set of 10 million Welsh words), with a functional design informed, from the outset, by representatives of all anticipated academic and community user groups.
Many (modernist) works of literature can be understood by their associativeness, be it constructed or “free”. This network-like character of (modernist) literature has often been addressed by terms like “free association”, connotation”, “context” or “intertext”. This paper proposes an experimental and exemplary approach to intraconnect a literary corpus of the Austrian writer Ilse Aichinger with semantic web-technologies to enable interactive explorations of word-associations.
This paper outlines the broad research context and rationale for a new international comparable corpus (ICC). The ICC is to be largely modelled on the text categories and their quantities the International Corpus of English with only a few changes. The corpus will initially begin with nine European languages but others may join in due course. The paper reports on those and other agreements made at the inaugural planning meeting in Prague on 22-23 June 2017. It also sets out the project’s goals for its first two years.
Complex linguistic phenomena, such as Clitic Climbing in Bosnian, Croatian and Serbian, are often described intuitively, only from the perspective of the main tendency. In this paper, we argue that web corpora currently offer the best source of empirical material for studying Clitic Climbing in BCS. They thus allow the most accurate description of this phenomenon, as less frequent constructions can be tracked only in big, well-annotated data sources. We compare the properties of web corpora for BCS with traditional sources and give examples of studies on CC based on web corpora. Furthermore, we discuss problems related to web corpora and suggest some improvements for the future.
This paper reports about current practice in a staged approach to the introduction of NLP principles and techniques for students of information science (IIM) and of international communication and translation (ICT) as part of their curricula. As most of these students are rather not familiar with computer science or, in the case of IIM students, linguistics, we see them as comparable with students of the humanities. We follow a blended learning strategy with lectures, online materials, tutorials, and screencasts. In the first two terms, we focus on linguistics and its formalisation, NLP tools and applications are then introduced from the third term on. The lectures are combined with tutorials and - since the summer term 2017 - with a set of screencasts.
This chapter investigates policies which shape the role of the German language in contemporary Estonia. Whereas German played for many centuries an important role as the language of the economic and cultural elite in Estonia, it severely declined in importance throughout the twentieth century. Mirrored on this historical background, the paper provides an overview of the current functions of German and attitudes towards it and it discusses how these functions and attitudes are influenced by policies of various actors from inside and outside Estonia. The paper argues that German continues to play a significant role: while German is no longer a lingua franca, it still enjoys a number of functions and prestige in clearly defined niches involving communication within German-speaking circles or between Estonians and Germans. The interplay of language policies of the Estonian and the German-speaking states as well as by semi-state and private institutions succeed in maintaining German as an additional language in contemporary Estonia.
While good results have been achieved for named entity recognition (NER) in supervised settings, it remains a problem that for low resource languages and less studied domains little or no labelled data is available. As NER is a crucial preprocessing step for many natural language processing tasks, finding a way to overcome this deficit in data remains of great interest. We propose a distant supervision approach to NER that is both language and domain independent where we automatically generate labelled training data using gazetteers that we previously extracted from Wikipedia. We test our approach on English, German and Estonian data sets and contribute further by introducing several successful methods to reduce the noise in the generated training data. The tested models beat baseline systems and our results show that distant supervision can be a promising approach for NER when no labelled data is available. For the English model we also show that the distant supervision model is better at generalizing within the same domain of news texts by comparing it against a supervised model on a different test set.
This paper presents a survey on hate speech detection. Given the steadily growing body of social media content, the amount of online hate speech is also increasing. Due to the massive scale of the web, methods that automatically detect hate speech are required. Our survey describes key areas that have been explored to automatically recognize these types of utterances using natural language processing. We also discuss limits of those approaches.
Most research on ethnicity has focused on visual cues. However, accents are strong social cues that can match or contradict visual cues. We examined understudied reactions to people whose one cue suggests one ethnicity, whereas the other cue contradicts it. In an experiment conducted in Germany, job candidates spoke with an accent either congruent or incongruent with their (German or Turkish) appearance. Based on ethnolinguistic identity theory, we predicted that accents would be strong cues for categorization and evaluation. Based on expectancy violations theory we expected that incongruent targets would be evaluated more extremely than congruent targets. Both predictions were confirmed: accents strongly influenced perceptions and Turkish-looking German-accented targets were perceived as most competent of all targets (and additionally most warm). The findings show that bringing together visual and auditory information yields a more complete picture of the processes underlying impression formation.
When appearance does not match accent: neural correlates of ethnicity-related expectancy violations
(2017)
Most research on ethnicity in neuroscience and social psychology has focused on visual cues. However, accents are central social markers of ethnicity and strongly influence evaluations of others. Here, we examine how varying auditory (vocal accent) and visual (facial appearance) information about others affects neural correlates of ethnicity-related expectancy violations. Participants listened to standard German and Turkish-accented speakers and were subsequently presented with faces whose ethnic appearance was either congruent or incongruent to these voices. We expected that incongruent targets (e.g. German accent/Turkish face) would be paralleled by a more negative N2 event-related brain potential (ERP) component. Results confirmed this, suggesting that incongruence was related to more effortful processing of both Turkish and German target faces. These targets were also subjectively judged as surprising. Additionally, varying lateralization of ERP responses for Turkish and German faces suggests that the underlying neural generators differ, potentially reflecting different emotional reactions to these targets. Behavioral responses showed an effect of violated expectations: German-accented Turkish-looking targets were evaluated as most competent of all targets. We suggest that bringing together neural and behavioral measures of expectancy violations, and using both visual and auditory information, yields a more complete picture of the processes underlying impression formation.
Language of Responsibility. The Influence of Linguistic Abstraction on Collective Moral Emotions
(2017)
Two experiments investigated the effects of linguistic abstractness on the experience of collective moral emotions. In Experiment 1 participants were presented with two scenarios about ingroup misbehavior, phrased using descriptive action verbs, interpretative action verbs, adjectives or nouns. The results show that participants experienced slightly more negative moral emotions with higher levels of linguistic abstractness. In Experiment 2 we also tested for the influence of national identification on the relationship between linguistic abstractness and emotional reactions. Additionally, we expanded the number of scenarios. Experiment 2 replicated the earlier pattern, but found larger differences between conditions. The strength of national identification did not moderate the observed effects. The results of this research are discussed within the context of the linguistic category model and psychology of collective moral emotions.
Syntactic theory has tended to vacillate between implausible methodological extremes. Some linguists hold that our theories are accountable solely for the corpus of attested utterances; others assume our subject matter is unobservable intuitive feelings about sentences. Both extremes should be rejected. The subject matter of syntax is neither past utterance production nor the functioning of inaccessible mental machinery; it is normative - a system of tacitly grasped constraints defining correctness of structure. There are interesting parallels between syntactic and moral systems, modulo the key difference that linguistic systems are diverse whereas morality is universal. The appropriate epistemology for justifying formulations of normative systems is familiar in philosophy: it is known as the method of reflective equilibrium.
Telicity and agentivity are semantic factors that split intransitive verbs into (at least two) different classes. Clear-cut unergative verbs, which select the auxiliary HAVE, are assumed to be atelic and agent-selecting; unequivocally unaccusative verbs, which select the auxiliary BE, are analyzed as telic and patient-selecting. Thus, agentivity and telicity are assumed to be inversely correlated in split intransitivity. We will present semantic and experimental evidence from German and Mandarin Chinese that casts doubts on this widely held assumption. The focus of our experimental investigation lies on variation with respect to agentivity (specifically motion control, manipulated via animacy), telicity (tested via a locative vs. goal adverbial), and BE/HAVE-selection with semantically flexible intransitive verbs of motion. Our experimental methods are acceptability ratings for German and Chinese (Experiments 1 and 2) and event-related potential (ERP) measures for German (Experiment 3). Our findings contradict the above-mentioned assumption that agentivity and telicity are generally inversely correlated and suggest that for the verbs under study, agentivity and telicity harmonize with each other. Furthermore, the ERP measures reveal that the impact of the interaction under discussion is more pronounced on the verb lexeme than on the auxiliary. We also found differences between Chinese and German that relate to the influence of telicity on BE/HAVE-selection. They seem to confirm the claim in previous research that the weight of the telicity factor locomotion (or internal motion) is cross-linguistically variable.