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The authors compare the use of two formats for requesting an object in informal everyday interaction: imperatives, common in our Polish data, and second-person polar questions, common in our English data. Imperatives and polar questions are selected in the same interactional “home environments” across the languages, in which they enact two social actions: drawing on shared responsibility and enlisting assistance, respectively. Speakers across the languages differ in their choice of request format in “mixed” interactional environments that support either. The finding shed light on the orderly ways in which cultural diversity is grounded in invariants of action formation.
An experiment on the English caused motion construction in adult- and child-directed speech was conducted to assess in how far (i) verbal frequency biases and (ii) a register-specific preference for explicit and redundant coding influence speakers' selection of argument structure constructions during speaking. Subjects retold the contents of short cartoon video clips to adult and child interaction partners. The stimuli showed events of caused motion which suggested designations with verbs for which caused motion-complementation was either (i) uncommon/unattested, (ii) conventional or (iii) the dominant usage in a sample extracted from the BNC. The results show a significant tendency to avoid more compacted coding (using the caused motion construction instead of a possible two-clause paraphrase) in child-directed speech. At the same time, they also point to an interaction between the register-specific preference for explicitness and verbs' relative conventionality in the construction that neutralizes the effect for verbs that are highly frequent in the target environment.
We examine predicative adjectives as an unsupervised criterion to extract subjective adjectives. We do not only compare this criterion with a weakly supervised extraction method but also with gradable adjectives, i.e. another highly subjective subset of adjectives that can be extracted in an unsupervised fashion. In order to prove the robustness of this extraction method, we will evaluate the extraction with the help of two different state-of-the-art sentiment lexicons (as a gold standard).
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.
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.
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.
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.
A frequently replicated finding is that higher frequency words tend to be shorter and contain more strongly reduced vowels. However, little is known about potential differences in the articulatory gestures for high vs. low frequency words. The present study made use of electromagnetic articulography to investigate the production of two German vowels, [i] and [a], embedded in high and low frequency words. We found that word frequency differently affected the production of [i] and [a] at the temporal as well as the gestural level. Higher frequency of use predicted greater acoustic durations for long vowels; reduced durations for short vowels; articulatory trajectories with greater tongue height for [i] and more pronounced downward articulatory trajectories for [a]. These results show that the phonological contrast between short and long vowels is learned better with experience, and challenge both the Smooth Signal Redundancy Hypothesis and current theories of German phonology.