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Sexual harassment severely impacts the educational system in the West African country Benin and the progress of women in this society that is characterized by great gender inequality. Knowledge of the belief systems rooting in the sociocultural context is crucial to the understanding of sexual harassment. However, no study has yet investigated how sexual harassment is related to fundamental beliefs in Benin or West African countries. We conducted a field study on 265 female and male students from several high schools in Benin to investigate the link between sexual harassment and measures of ambivalent sexism, gender identity, and rape myth acceptance. Almost half of the sample reported having experienced sexual harassment personally or among peers. Levels of sexism and rape myth acceptance were very high compared to other studies. These attitudes appeared to converge in a sexist belief system that was linked to personal experiences, the perceived probability of experiencing and fear of sexual harassment. Results suggest that sexual harassment is a societal problem and that interventions need to address fundamental attitudes held in societies low in gender equality.
Drawing on naturalistic video and audio recordings of international meetings, and within the framework of conversation analysis, ethnomethodology and interactional linguistics, this chapter studies how multilingual resources are mobilized in social interactions among professionals, how available linguistic and embodied resources are identified and used by the participants, which solutions are locally elaborated by them when they are confronted with various languages spoken but not shared among them, and which definition of multilingualism they adopt for all practical purposes. Focusing on the multilingual solutions emically elaborated in international professional meetings, we show that the participants orient to a double principle: on the one hand, they orient to the progressivity of the interaction, adopting all the possible resources that enable them to go on within the current activity; on the other hand, they orient to the intersubjectivity of the interaction, treating, preventing and repairing possible troubles and problems of understanding. Specific multilingual solutions can be adopted to keep this difficult balance between progressivity and intersubjectivity; they vary according to the settings, the competences at hand, the linguistic and embodied resources locally defined by the participants as publicly available, the multilingual resources treated as totally or partially shared, as transparent or opaque, and as needing repair or not. The paper begins by sketching the analytical framework, including the methodology and the data collected; it then presents some general findings, before offering an analysis of various ways in which participants keep the balance between progressivity and intersubjectivity in different multilingual interactional contexts.
Dropping out of overlap is a frequent practice for overlap resolution (Schegloff, 2000, Jefferson, 2004) in interaction, as it re-establishes the “one-at-a-time” principle of the turn-taking system (Sacks et al., 1974). While it is appropriate to analyze the practice of dropping out of overlap as a verbal and thus audible phenomenon, a close look at video data reveals that withdrawing from an action trajectory is also an embodied practice. Based on a fine-grained multimodal analysis (C. Goodwin, 1981, Mondada, 2007a, Mondada, 2007b) of videotaped interactions in French, this paper illustrates how overlapped speakers organize the momentary suspension of their action trajectory in visible ways. Indeed, participants do not instantly withdraw from their action trajectory when they stop talking. By using bodily resources, they are able to display continuous monitoring of the availability of their co-participants and of the next possible slot for resuming their suspended action. I therefore suggest analyzing the drop out of overlap as the first step of withdrawal, as definitive, embodied withdrawal can occur later, or, in case of resumption, not at all. Consequently, my paper analyzes withdrawal as a good example of strengthening the analytic concept of embodiment with regard to turn-taking practices in interaction.
In the rapidly changing circumstances of our increasingly digital world, reading is also becoming an increasingly digital experience: electronic books (e-books) are now outselling print books in the United States and the United Kingdom. Nevertheless, many readers still view e-books as less readable than print books. The present study thus used combined EEG and eyetracking measures in order to test whether reading from digital media requires higher cognitive effort than reading conventional books. Young and elderly adults read short texts on three different reading devices: a paper page, an e-reader and a tablet computer and answered comprehension questions about them while their eye movements and EEG were recorded. The results of a debriefing questionnaire replicated previous findings in that participants overwhelmingly chose the paper page over the two electronic devices as their preferred reading medium. Online measures, by contrast, showed shorter mean fixation durations and lower EEG theta band voltage density – known to covary with memory encoding and retrieval – for the older adults when reading from a tablet computer in comparison to the other two devices. Young adults showed comparable fixation durations and theta activity for all three devices. Comprehension accuracy did not differ across the three media for either group. We argue that these results can be explained in terms of the better text discriminability (higher contrast) produced by the backlit display of the tablet computer. Contrast sensitivity decreases with age and degraded contrast conditions lead to longer reading times, thus supporting the conclusion that older readers may benefit particularly from the enhanced contrast of the tablet. Our findings thus indicate that people’s subjective evaluation of digital reading media must be dissociated from the cognitive and neural effort expended in online information processing while reading from such devices.
In this article, we examine the effectiveness of bootstrapping supervised machine-learning polarity classifiers with the help of a domain-independent rule-based classifier that relies on a lexical resource, i.e., a polarity lexicon and a set of linguistic rules. The benefit of this method is that though no labeled training data are required, it allows a classifier to capture in-domain knowledge by training a supervised classifier with in-domain features, such as bag of words, on instances labeled by a rule-based classifier. Thus, this approach can be considered as a simple and effective method for domain adaptation. Among the list of components of this approach, we investigate how important the quality of the rule-based classifier is and what features are useful for the supervised classifier. In particular, the former addresses the issue in how far linguistic modeling is relevant for this task. We not only examine how this method performs under more difficult settings in which classes are not balanced and mixed reviews are included in the data set but also compare how this linguistically-driven method relates to state-of-the-art statistical domain adaptation.
Based on German speaking data from various activity types, the range of multimodal resources used to construct turn-beginnings is reviewed. It is claimed that participants in talk-in-interaction need to deal with four tasks in order to construct a turn which precisely fits the interactional moment of its production:
1. Achieve joint orientation: The accomplishment of the socio-spatial prerequisites necessary for producing a turn which is to become part of the participants’ common ground.
2. Display uptake: Next speaker needs to display his/her understanding of the interaction so far as the backdrop on which the production of the upcoming turn is based.
3. Deal with projections from prior talk: The speaker has to deal with projections which have been established by (the) previous turn(s) with respect to the upcoming turn.
4. Project properties of turn-in-progress: The speaker needs to orient the recipient to properties of the turn s/he is about to produce.
Turn-design thus can be seen to be informed by tasks related to the multimodal, embodied, and interactive contingencies of online-construction of turns. The four tasks are ordered in terms of prior tasks providing the prerequisite for accomplishing a later task.
Opinion holder extraction is one of the most important tasks in sentiment analysis. We will briefly outline the importance of predicates for this task and categorize them according to part of speech and according to which semantic role they select for the opinion holder. For many languages there do not exist semantic resources from which such predicates can be easily extracted. Therefore, we present alternative corpus-based methods to gain such predicates automatically, including the usage of prototypical opinion holders, i.e. common nouns, denoting for example experts or analysts, which describe particular groups of people whose profession or occupation is to form and express opinions towards specific items.
We explore the feasibility of contextual healthiness classification of food items. We present a detailed analysis of the linguistic phenomena that need to be taken into consideration for this task based on a specially annotated corpus extracted from web forum entries. For automatic classification, we compare a supervised classifier and rule-based classification. Beyond linguistically motivated features that include sentiment information we also consider the prior healthiness of food items.
We investigate the task of detecting reliable statements about food-health relationships from natural language texts. For that purpose, we created a specially annotated web corpus from forum entries discussing the healthiness of certain food items. We examine a set of task-specific features (mostly) based on linguistic insights that are instrumental in finding utterances that are commonly perceived as reliable. These features are incorporated in a supervised classifier and compared against standard features that are widely used for various tasks in natural language processing, such as bag of words, part-of speech and syntactic parse information.