Quantitative assessment of information quality in textual sources for landslide inventories

Landslide research chiefly relies on digital inventories for a multitude of spatial, temporal, and/or process analyses. In respect thereof, many landslide inventories are populated with information from textual documents (e.g., news articles, technical reports) due to effectiveness. However, information detail can vary greatly in these documents and the question arises whether such textual information is suitable for landslide inventories. The present work proposes to define the usefulness of textual source types as a probability to find landslide information, weighted with adaptable parameter requirements. To illustrate the method with practical results, a German landslide dataset has been examined. It was found that three combined source types (administrative documents, expert opinions, and news articles) give an 89 % chance to detect useful information on three defined parameters (location, date, and process type). In conclusion, the definition of usefulness as a probability makes it an intuitive, quantitative measure that is suitable for a wide range of applicants. Furthermore, a priori knowledge of usefulness allows for focusing on a few source types with the most promising outcome and thus increases the effectiveness of textual data acquisition and digitalisation for landslide inventories.

Pantomyma Theater as a Phenomenon of Modern Spectacular Culture: Specifics of Additional Transmission Channels

The article reveals the peculiarities of the representation of pantomime theaters in the conditions of new broadcasting channels (on the example of Internet sites and social networks), as well as theorizes socio-cultural conditions that at the present stage determine communication in pantomime theater. The study found that modern pantomime theater, as a phenomenon of entertainment culture, actively represents itself in the network space, which has become an additional channel for broadcasting performances, expanding the boundaries of the audience and providing other opportunities for viewing; rethinks the relationship with the viewer, his role in communication, as well as his own place in the modern world. It is shown that social networks and Internet sites are important platforms for self-presentation of pantomime directors and spectators, discussion and formation of possible directions for further development. In addition to photos and videos (photos of troupe members, videos of pantomimes, videos from tours and festivals), the theaters' websites provide textual information about the history of the group and the theater's activities at the present stage, textual annotations of performances, reviews and forms of communication.

Mutual impact of acoustic and linguistic representations for continuous emotion recognition in call-center conversations

<div> <div> <div> <p>The goal of our research is to automaticaly retrieve the satisfaction and the frustration in real-life call-center conversations. This study focuses an industrial application in which the customer satisfaction is continuously tracked down to improve customer services. To compensate the lack of large annotated emotional databases, we explore the use of pre-trained speech representations as a form of transfer learning towards AlloSat corpus. Moreover, several studies have pointed out that emotion can be detected not only in speech but also in facial trait, in biological response or in textual information. In the context of telephone conversations, we can break down the audio information into acoustic and linguistic by using the speech signal and its transcription. Our experiments confirms the large gain in performance obtained with the use of pre-trained features. Surprisingly, we found that the linguistic content is clearly the major contributor for the prediction of satisfaction and best generalizes to unseen data. Our experiments conclude to the definitive advantage of using CamemBERT representations, however the benefit of the fusion of acoustic and linguistic modalities is not as obvious. With models learnt on individual annotations, we found that fusion approaches are more robust to the subjectivity of the annotation task. This study also tackles the problem of performances variability and intends to estimate this variability from different views: weights initialization, confidence intervals and annotation subjectivity. A deep analysis on the linguistic content investigates interpretable factors able to explain the high contribution of the linguistic modality for this task. </p> </div> </div> </div>

Mutual impact of acoustic and linguistic representations for continuous emotion recognition in call-center conversations

<div> <div> <div> <p>The goal of our research is to automaticaly retrieve the satisfaction and the frustration in real-life call-center conversations. This study focuses an industrial application in which the customer satisfaction is continuously tracked down to improve customer services. To compensate the lack of large annotated emotional databases, we explore the use of pre-trained speech representations as a form of transfer learning towards AlloSat corpus. Moreover, several studies have pointed out that emotion can be detected not only in speech but also in facial trait, in biological response or in textual information. In the context of telephone conversations, we can break down the audio information into acoustic and linguistic by using the speech signal and its transcription. Our experiments confirms the large gain in performance obtained with the use of pre-trained features. Surprisingly, we found that the linguistic content is clearly the major contributor for the prediction of satisfaction and best generalizes to unseen data. Our experiments conclude to the definitive advantage of using CamemBERT representations, however the benefit of the fusion of acoustic and linguistic modalities is not as obvious. With models learnt on individual annotations, we found that fusion approaches are more robust to the subjectivity of the annotation task. This study also tackles the problem of performances variability and intends to estimate this variability from different views: weights initialization, confidence intervals and annotation subjectivity. A deep analysis on the linguistic content investigates interpretable factors able to explain the high contribution of the linguistic modality for this task. </p> </div> </div> </div>

Predicting standardized absolute returns using rolling-sample textual modelling

Understanding how textual information impacts financial market volatility has been one of the growing topics in financial econometric research. In this paper, we aim to examine the relationship between the volatility measure that is extracted from GARCH modelling and textual news information both publicly available and from subscription, and the performances of the two datasets are compared. We utilize a latent Dirichlet allocation method to capture the dynamic features of the textual data overtime by summarizing their statistical outputs, such as topic distributions in documents and word distributions in topics. In addition, we transform various measures representing the popularity and diversity of topics to form predictors for a rolling regression model to assess the usefulness of textual information. The proposed method captures the statistical properties of textual information over different time periods and its performance is evaluated in an out-of-sample analysis. Our results show that the topic measures are more useful for predicting our volatility proxy, the unexplained variance from the GARCH model than the simple moving average. The finding indicates that our method is helpful in extracting significant textual information to improve the prediction of stock market volatility.

Graphological and semantic foregrounding as affecting gaze and speech of impulsive and reflective readers

The study explores the effects of graphological and semantic foregrounding on speech and gaze behavior in textual information construal of subjects with higher and lower impulsivity. Eye movements of sixteen participants were recorded as they read drama texts with interdiscourse switching (semantic foregrounding), with features of typeface distinct from the surrounding text (graphological foregrounding). Discourse modification patterns were analyzed and processed in several steps: specification of participant/object/action/event/perspective modification, parametric annotation of participants’ discourse responses, contrastive analysis of modification parameter activity and parameter synchronized activity. Significant distinctions were found in eye movement parameters (gaze count and initial fixation duration) in subjects with higher and lower impulsivity when reading parts of text with graphical foregrounding. Impulsive subjects tended to visit the areas more often with longer initial fixations than reflective subjects, which is explained in terms of stimulus-driven attention, associated with bottom-up processes. However, these differences in gaze behavior did not result in pronounced distinctions in discourse responses, which were only slightly mediated by impulsivity/reflectivity.

Creative communication of artistic systems M. Tsvetaeva and B. Pasternak

This article proceeds from the fact that the problem of interaction and mutual influence is quite acute in literary studies. In this regard, the relevance of the research is due, firstly, to the correspondence to the priority direction of modern literary studies associated with the comparative analysis of the text, and secondly, to the need to disclose the deep theoretical and artistic content of creative communication of such artistic personalities of the XX century as M. Tsvetaeva and B. Pasternak, whose legacy still contains many lacunae. The methodological basis of the research is an integrated approach, including comparative-historical, historical-literary, comparative-typological, system-analytical and biographical methods, as well as the method of comparative studies, which allows to study literary analogies and connections of different national literatures, their refraction in the texts of the authors studied. Hermeneutics contributed to the mental comprehension of the analyzed texts, the mental processing of textual information. An important episode in the history of world poetry was the correspondence-dialogue of iconic poets for their time: M. Tsvetaeva and B. Pasternak. Correspondence is valuable not only because it shows us the life of poets in relation to time. The creative aspect of correspondence is very important. The rapprochement manifested in it and at the same time the repulsion was deeply creative and left deep traces in the legacy of all its participants. Poets, albeit to varying degrees, concentrated and passionately, sought to define for themselves the essence of life and poetry. In the course of the research, the author of the article comes to the conclusion that, firstly, the literary process is characterized by a systematic nature in which authors and their works are in certain relationships to each other. Secondly, the thirteen-year correspondence of M. Tsvetaeva with B. Pasternak was very significant for literature. Thanks to mutual communication, creative interaction, the poets created unique, emotionally deep works.

Text-based Recommendation Systems for Software Developers: A Systematic Literature Review

Purpose: The aim of this SLR is to look at recommendation systems which receive textual information as an input. By analysing them it is possible to understand how the textual information is preprocessed and which algorithms are then used to generate recommendations. Methods: With the Search Query I frst identifed 487 papers, from which 65 were removed as duplicates. After the IC and EC application, 28 articles remained as relevant. Results: From these articles’ analysis, it was found that the most commonly used pre-processing techniques are tokenization, TF-IDF, and stopwords removal. I also determined that all algorithms for suggestions generation in such systems can be divided into 4 categories: classifcation, ranking, clustering, and heuristic-based algorithms. In the last step I found that the most frequent output of such systems are API, code, and workers suggestions. Conclusion: With this work, I looked at which pre-processing techniques are used in the text-based recommender systems for software developers and which are the most common. I have also looked at the classifcation of algorithms for such recommendation systems. Finally, I considered what kind of objects are recommended by these text-based recommendation systems.

Using Inverted Index for Fingerprint Search

Fingerprints are the most used biometric information for identifying people. With the increase in fingerprint data, indexing techniques are essential to perform an efficient search. In this work, we devise a solution that applies traditional inverted index, widely used in textual information retrieval, for fingerprint search. For that, it first converts fingerprints to text documents using techniques, such as Minutia Cylinder-Code and Locality-Sensitive Hashing, and then indexes them in inverted files. In the experimental evaluation, our approach obtained 0.42% of error rate with 10% of penetration rate in the FVC2002 DB1a data set, surpassing some established methods.

Readability as a measure of textual complexity: determinants and evidence in Brazilian companies

ABSTRACT The aim of this article was to evaluate the effect of company earnings and of harmonization with IFRS on the readability of Management Reports in the Brazilian stock market. There is a gap to be filled both in the elaboration and adaptation of readability measures to the context studied, as the studies tend to replicate the original formulas, and in identifying the determinants of the readability of Brazilian company reports, as the research in this field remains in its infancy and the results are inconclusive. The results provide indications for investors to identify complex textual information and may help public policymakers to establish a simple writing manual, along the lines of the SEC’s 1998 Plain English Handbook. The modified metrics and the one developed overcome the criticisms regarding the use of readability formulas in accounting research and could be used in substitution of the original metrics in future studies. An econometric model was used that presents the determinants of readability. Readability was calculated for the Results Analysis section of the Management Report. The resulting construct is understood via three attributes: persistence, current performance, and the reference benchmark. Harmonization with IFRS is a dummy variable, which delimits the pre- and post-IFRS periods. The hypotheses were tested in a sample of Brazilian companies made up of 714 company-year observations covering the period from 2006 to 2019. The descriptive results show that there is an apparent improvement in the readability of the reports in the pre- and post-IFRS period comparison. The econometric evidence shows that, in general, companies with persistent and positive earnings present less complex reports and are more likely to have highly readable reports, because managers publish reports with better readability to signal positive results to the market.