Search results for: text information retrieval

Authors: Mary Cruz

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Founded from 1496 to 1502, Santo Domingo is the oldest European settlement in the Americas, inhabited without any discontinuity and was the first seat of Spanish power in the new world. Capital of the country since 1932.In this text, we discover Santo Domingo as an international tourist center, Urban Structure, Eco-tourism, Contamination and other issues related to tourism and development of this city. Founded from 1496 to 1502, Santo Domingo is the oldest European settlement in the Americas, inhabited without any discontinuity and was the first seat of Spanish power in the new world. Capital of the country since 1932. Encouraged by the United Nations and the World Bank, many Caribbean governments have encouraged tourism from the 1950s to boost their Third World economies. In this text, we discover Santo Domingo as an international tourist center, Urban Structure, Eco-tourism, Contamination and challenges of the first tourist destination in the Caribbean.

Keywords: eco-tourism, urban structure, contamination, development

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Authors: Yasmin Tantawi, Mary Beth Rosson

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In response to the dearth of information about emoji use for different purposes in different settings, this paper investigates the paralinguistic function of emojis within Twitter communication in the United States. To conduct this investigation, the Twitter feeds from 16 population centers spread throughout the United States were collected from the Twitter public API. One hundred tweets were collected from each population center, totaling to 1,600 tweets. Tweets containing emojis were next extracted using the “emot” Python package; these were then analyzed via the IBM Watson API Natural Language Understanding module to identify the topics discussed. A manual content analysis was then conducted to ascertain the paralinguistic and emotional features of the emojis used in these tweets. We present our characterization of emoji usage in Twitter and discuss implications for the design of Twitter and other text-based communication tools.

Keywords: computer-mediated communication, content analysis, paralinguistics, sociology

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Authors: Alejandra G. Barbón, José Vila, Dania Vazquez

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This study seeks to contribute to the advancement of library and archival sciences in the areas of records management, knowledge organization, and information architecture, particularly focusing on the enhancement of bibliographical description through the incorporation of visual interactive designs aimed to enrich the library users’ experience. In an era of heightened awareness about the legacy of hiddenness across special and rare collections in libraries and archives, along with the need for inclusivity in academia, the University of Miami Libraries has embarked on an innovative project that intersects the realms of print culture, decolonization, and digital technology. This proposal presents an exciting initiative to revitalize the study of Artists’ Books collections by employing digital visual representations to decolonize bibliographic records of some of the most unique materials and foster a more holistic understanding of cultural heritage. Artists' Books, a dynamic and interdisciplinary art form, challenge conventional bibliographic classification systems, making them ripe for the exploration of alternative approaches. This project involves the creation of a digital platform that combines multimedia elements for digital representations, interactive information retrieval systems, innovative information architecture, trending bibliographic cataloging and metadata initiatives, and collaborative curation to transform how we engage with and understand these collections. By embracing the potential of technology, we aim to transcend traditional constraints and address the historical biases that have influenced bibliographic practices. In essence, this study showcases a groundbreaking endeavor at the University of Miami Libraries that seeks to not only enhance bibliographic practices but also confront the legacy of hiddenness across special and rare collections in libraries and archives while strengthening conventional bibliographic description. By embracing digital visualizations, we aim to provide new pathways for understanding Artists' Books collections in a manner that is more inclusive, dynamic, and forward-looking. This project exemplifies the University’s dedication to fostering critical engagement, embracing technological innovation, and promoting diverse and equitable classifications and representations of cultural heritage.

Keywords: decolonizing bibliographic cataloging frameworks, digital visualizations information architecture platforms, collaborative curation and inclusivity for records management, engagement and accessibility increasing interaction design and user experience

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Authors: Nei-Ching Yeh

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This study describes undergraduate casual-leisure information behaviors relevant to online videos. Diaries and in-depth interviews were used to collect data. Twenty-four undergraduates participated in this study (9 men, 15 women; all were aged 18–22 years). This study presents a model of casual-leisure information behaviors and contributes new insights into user experience in casual-leisure settings, such as online video programs, with implications for other information domains.

Keywords: casual-leisure information behaviors, information behavior, online videos, role

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Authors: Tharini N. de Silva, Xiao Zhibo, Zhao Rui, Mao Kezhi

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Causal relation identification is a crucial task in information extraction and knowledge discovery. In this work, we present two approaches to causal relation identification. The first is a classification model trained on a set of knowledge-based features. The second is a deep learning based approach training a model using convolutional neural networks to classify causal relations. We experiment with several different convolutional neural networks (CNN) models based on previous work on relation extraction as well as our own research. Our models are able to identify both explicit and implicit causal relations as well as the direction of the causal relation. The results of our experiments show a higher accuracy than previously achieved for causal relation identification tasks.

Keywords: causal realtion extraction, relation extracton, convolutional neural network, text representation

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Authors: Ali Akbar

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The importance of advancing women’s rights is closely intertwined with the development of civil society and the institutionalization of democracy in Middle Eastern countries. There is indeed an intimate relationship between the process of democratization and promoting gender equality, since democracy necessitates equality between men and women. In order to advance the issue of gender equality, what is required is a solid theoretical framework which has its roots in the reexamination of pre-modern interpretation of certain Qurʾānic passages that seem to have given men more rights than it gives women. This paper suggests that those Muslim scholars who adopt a contextualist approach to the Qurʾānic text and its interpretation provide a solid theoretical background for improving women’s rights. Indeed, the aim of the paper is to discuss how the contextualist approach to the Qurʾānic text and its interpretation given by a number of prominent scholars is capable of promoting the issue of gender equality. The paper concludes that since (1) much of the gender inequality found in the primary sources of Islam as well as pre-modern Muslim writings is rooted in the natural cultural norms and standards of early Islamic societies and (2) since the context of today’s world is so different from that of the pre-modern era, the proposed models provide a solid theoretical framework for promoting women’s rights and gender equality.

Keywords: contextualism, gender equality, Islam, the rights of women

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Authors: Jin Gang Lee, Hyun-Soo Lee, Moonseo Park

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The utilization of BIM and IFC allows project participants to collaborate across different areas by consistently sharing interoperable product information represented in a model. Comments or markups generated during the coordination process can be categorized as communication information, which can be shared in less standardized manner. It can be difficult to manage and reuse such information compared to the product information in a model. The present study proposes an interoperable coordination method using BCF (the BIM Collaboration Format) for managing and sharing the communication information during BIM based coordination process. A management function for coordination in the BIM collaboration system is developed to assess its ability to share the communication information in BIM collaboration projects. This approach systematically links communication information during the coordination process to the building model and serves as a type of storage system for retrieving knowledge created during BIM collaboration projects.

Keywords: design coordination, building information model, BIM collaboration format, industry foundation classes

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Authors: Aliya Grig, Konstantin Sokolov, Igor Shatalin

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The report describes the methodology for collecting data and building an ML model for determining the personality psychotype using profiling and personality traits methods based on several short messages of a user communicating on an arbitrary topic with a chitchat bot. In the course of the experiments, the minimum amount of text was revealed to confidently determine aspects of personality. Model accuracy - 85%. Users' language of communication is English. AI for a personalized communication with a user based on his mood, personality, and current emotional state. Features investigated during the research: personalized communication; providing empathy; adaptation to a user; predictive analytics. In the report, we describe the processes that captures both structured and unstructured data pertaining to a user in large quantities and diverse forms. This data is then effectively processed through ML tools to construct a knowledge graph and draw inferences regarding users of text messages in a comprehensive manner. Specifically, the system analyzes users' behavioral patterns and predicts future scenarios based on this analysis. As a result of the experiments, we provide for further research on training AI models to be empathetic, creating personalized communication for a user

Keywords: AI, empathetic, chatbot, AI models

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Authors: Annamarija Paula

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Modern psychology is divided into three distinct domains: cognition, affect, and conation. Historically, psychology devalued the importance of studying the effect in order to explain human behavior as it supposedly lacked both rational thought and a scientific foundation. As a result, affect remained the least studied domain for years to come. However, the last 30 years have marked a significant change in perspective, claiming that not only is affect highly adaptive, but it also plays a crucial role in cognitive processes. Affective states have a crucial impact on human behavior, which led to fundamental advances in the study of affective states on perception and judgment. Positive affect and negative affect are distinct entities and have different effects on social information processing. In addition, emotions of the same valence are manifested in distinct and unique physiological reactions indicating that not all forms of positive or negative affect are the same or serve the same purpose. The effect plays a vital role in perception and judgments, which impacts the validity and reliability of memory retrieval. The research paper analyzes key findings from the past three decades of observational and empirical research on affective states and cognition. The paper also addresses the limitations connected to the findings and proposes suggestions for possible future research.

Keywords: memory, affect, perception, judgement, mood congruency effect

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Authors: Ekaterina Lukianchenko

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The present article addresses the nuances of teaching English vocabulary to Russian-speaking students. The experiment involving 39 participants aged 17 to 21 proves that the key to understanding spoken coinages is not only the knowledge of their constituents, but rather the understanding of the context and co-text. The volunteers who took part knew the constituents, but did not know the meaning of the words. The assumption of the authors consists in the fact that the structure of the concept has a direct relation with the form of the particular vocabulary unit, but its form is secondary to its meaning, if the word is a spoken coinage, which is partly proved by the fact that in modern slang words have multiple meanings, as well as one notion can have various embodiments that have virtually nothing in common. The choice of vocabulary items that youngsters use is not exactly arbitrary, but, even if complex nominals are taken into consideration, whose meaning seems clear, as it looks like a sum of their constituents’ meanings, they are still impossible to understand without any context or co-text, as a lot of them are idiomatic, non-transparent. It is further explained what methods might be effective in teaching students how to deal with new words they encounter in real-life situations and how student’s knowledge of vocabulary might be enhanced.

Keywords: spoken language, cognitive linguistics, complex nominals, nominals with the incorporated object, concept, EFL, communicative language teaching

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Authors: Danielle Shackley, Yetunde Folajimi

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As more people turn to the internet seeking health-related information, there is more risk of finding false, inaccurate, or dangerous information. Sentiment analysis is a natural language processing technique that assigns polarity scores to text, ranging from positive, neutral, and negative. In this research, we evaluate the weight of a sentiment analysis feature added to fake health news classification models. The dataset consists of existing reliably labeled health article headlines that were supplemented with health information collected about COVID-19 from social media sources. We started with data preprocessing and tested out various vectorization methods such as Count and TFIDF vectorization. We implemented 3 Naive Bayes classifier models, including Bernoulli, Multinomial, and Complement. To test the weight of the sentiment analysis feature on the dataset, we created benchmark Naive Bayes classification models without sentiment analysis, and those same models were reproduced, and the feature was added. We evaluated using the precision and accuracy scores. The Bernoulli initial model performed with 90% precision and 75.2% accuracy, while the model supplemented with sentiment labels performed with 90.4% precision and stayed constant at 75.2% accuracy. Our results show that the addition of sentiment analysis did not improve model precision by a wide margin; while there was no evidence of improvement in accuracy, we had a 1.9% improvement margin of the precision score with the Complement model. Future expansion of this work could include replicating the experiment process and substituting the Naive Bayes for a deep learning neural network model.

Keywords: sentiment analysis, Naive Bayes model, natural language processing, topic analysis, fake health news classification model

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Authors: Faiza Belbachir, Thibault Schienhinski

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The massive development of online social networks allows users to post and share their opinions on various topics. With this huge volume of opinion, it is interesting to extract and interpret these information for different domains, e.g., product and service benchmarking, politic, system of recommendation. This is why opinion detection is one of the most important research tasks. It consists on differentiating between opinion data and factual data. The difficulty of this task is to determine an approach which returns opinionated document. Generally, there are two approaches used for opinion detection i.e. Lexical based approaches and Machine Learning based approaches. In Lexical based approaches, a dictionary of sentimental words is used, words are associated with weights. The opinion score of document is derived by the occurrence of words from this dictionary. In Machine learning approaches, usually a classifier is trained using a set of annotated document containing sentiment, and features such as n-grams of words, part-of-speech tags, and logical forms. Majority of these works are based on documents text to determine opinion score but dont take into account if these texts are really correct. Thus, it is interesting to exploit other information to improve opinion detection. In our work, we will develop a new way to consider the opinion score. We introduce the notion of trust score. We determine opinionated documents but also if these opinions are really trustable information in relation with topics. For that we use lexical SentiWordNet to calculate opinion and trust scores, we compute different features about users like (numbers of their comments, numbers of their useful comments, Average useful review). After that, we combine opinion score and trust score to obtain a final score. We applied our method to detect trust opinions in TRIPADVISOR collection. Our experimental results report that the combination between opinion score and trust score improves opinion detection.

Keywords: Tripadvisor, opinion detection, SentiWordNet, trust score

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Authors: Abdullah Karaman, Kursad Sayin

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In this research, which information technologies are used in small hotel businesses, and the information technologies-performance perception of the managers are pointed out. During the research, the questionnaire was prepared and the small scale hotel managers were interviewed face to face and they filled out the questionnaire and the answers acquired were evaluated. As the result of the research, it was obtained that the managers do not care much about the information technologies usage in practice even though they accepted that the information technologies are important in terms of performance.

Keywords: information technologies, managers, performance, small hotels

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Authors: Mawloud Mosbah, Bachir Boucheham

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We present here the results for a comparative study of some techniques, available in the literature, related to the relevance feedback mechanism in the case of a short-term learning. Only one method among those considered here is belonging to the data mining field which is the K-Nearest Neighbours Algorithm (KNN) while the rest of the methods is related purely to the information retrieval field and they fall under the purview of the following three major axes: Shifting query, Feature Weighting and the optimization of the parameters of similarity metric. As a contribution, and in addition to the comparative purpose, we propose a new version of the KNN algorithm referred to as an incremental KNN which is distinct from the original version in the sense that besides the influence of the seeds, the rate of the actual target image is influenced also by the images already rated. The results presented here have been obtained after experiments conducted on the Wang database for one iteration and utilizing colour moments on the RGB space. This compact descriptor, Colour Moments, is adequate for the efficiency purposes needed in the case of interactive systems. The results obtained allow us to claim that the proposed algorithm proves good results; it even outperforms a wide range of techniques available in the literature.

Keywords: CBIR, category search, relevance feedback, query point movement, standard Rocchio’s formula, adaptive shifting query, feature weighting, original KNN, incremental KNN

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Authors: Xiang Shijie, Zhou Dong, Tian Dan

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Speaker recognition is a crucial task in the field of speech processing, aimed at identifying individuals based on their vocal characteristics. However, existing speaker recognition methods face numerous challenges. Traditional methods primarily rely on audio signals, which often suffer from limitations in noisy environments, variations in speaking style, and insufficient sample sizes. Additionally, relying solely on audio features can sometimes fail to capture the unique identity of the speaker comprehensively, impacting recognition accuracy. To address these issues, we propose a multi-modal network architecture that simultaneously processes both audio and text signals. By gradually integrating audio and text features, we leverage the strengths of both modalities to enhance the robustness and accuracy of speaker recognition. Our experiments demonstrate significant improvements with this multi-modal approach, particularly in complex environments, where recognition performance has been notably enhanced. Our research not only highlights the limitations of current speaker recognition methods but also showcases the effectiveness of multi-modal fusion techniques in overcoming these limitations, providing valuable insights for future research.

Keywords: feature fusion, memory network, multimodal input, speaker recognition

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Authors: Aditya Jayadas

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During a pandemic like the one we are in with COVID-19, older adults, especially those who live in a senior retirement facility, experience even bigger challenges as they are often dependent on other individuals for care. Many older adults are dependent on caregivers to assist with their instrumented activities of daily living (IADL). With travel restrictions imposed during a pandemic, there is a critical need to ensure that older adults who are homebound continue to be able to participate in physical exercise, cognitive exercise, and social interaction programs. The objective of this study was to better understand the challenges that older adults faced during the pandemic and what they were doing specifically to cope with the pandemic physically, mentally, and through social interaction. A focus group was conducted with ten older adults (age: 82.70 ± 7.81 years; nine female and one male) who resided in a senior retirement facility. During the course of one hour, seven open-ended questions were posed to the participants: a) What has changed in your life since the start of the pandemic, b) What has been most challenging for you, c) What are you doing to take care of yourself, d) Are you doing anything specifically as it relates to your physical health, e) Are you doing anything specifically as it relates to your mental health, f) What did you do for social interaction during the pandemic, g) Is there anything else you would like to share as it relates to your experience during the pandemic. The focus group session was audio-taped, and verbatim transcripts were created to evaluate the responses of the participants. The transcript consisted of 4,698 words and 293 lines of text. The data was analyzed using content analysis. The unit of analysis was the text from the audio recordings that were transcribed. From the review of the transcribed text, themes and sub-themes were identified, along with salient quotes under each sub-theme. The major themes that emerged from the data were: having a routine, engaging in activities, attending exercise classes, use of technology, family, community, and prayer. The quotes under the sub-themes provided compelling evidence of how older adults coped during the pandemic while addressing the challenges they faced and developing strategies to address their physical and mental health while interacting with others. Lessons learned from this focus group can be used to develop specific physical exercise, cognitive exercise, and social interaction programs that benefit the health and well-being of older adults.

Keywords: cognitive exercise, pandemic, physical exercise, social interaction

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Authors: Te-Jen Chang, I-Hui Pan, Kuang-Hsiung Tan, Shan-Jen Cheng, Chien-Wu Lan, Chih-Chan Hu

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With the event of multimedia age in order to protect data not to be tampered, damaged, and faked, information hiding technologies are proposed. Information hiding means important secret information is hidden into cover multimedia and then camouflaged media is produced. This camouflaged media has the characteristic of natural protection. Under the undoubted situation, important secret information is transmitted out.Reversible information hiding technologies for high capacity is proposed in this paper. The gray images are as cover media in this technology. We compress gray images and compare with the original image to produce the estimated differences. By using the estimated differences, expression information hiding is used, and higher information capacity can be achieved. According to experimental results, the proposed technology can be approved. For these experiments, the whole capacity of information payload and image quality can be satisfied.

Keywords: cover media, camouflaged media, reversible information hiding, gray image

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Authors: Amin Pashaye Amiri

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Freedom of information, according to which the public has a right to have access to government-held information, is largely considered as a tool for improving transparency and accountability in governments, and as a requirement of self-governance and good governance. So far, more than ninety countries have recognized citizens’ right to have access to public information. This recognition often took place through the adoption of an act referred to as “freedom of information act”, “access to public records act”, and so on. A freedom of information act typically imposes a positive obligation on a government to initially and regularly release certain public information, and also obliges it to provide individuals with information they request. Such an act usually allows governmental bodies to withhold information only when it falls within a limited number of exemptions enumerated in the act such as exemptions for protecting privacy of individuals and protecting national security. Some steps have been taken at the national and international level towards the recognition of freedom of information as a human right. Freedom of information was recognized in a few countries as a part of freedom of expression, and therefore, as a human right. Freedom of information was also recognized by some international bodies as a human right. The Inter-American Court of Human Rights ruled in 2006 that Article 13 of the American Convention on Human Rights, which concerns the human right to freedom of expression, protects the right of all people to request access to government information. The European Court of Human Rights has recently taken a considerable step towards recognizing freedom of information as a human right. However, in spite of the measures that have been taken, public access to government information is not yet widely accepted as an international human right. The paper will consider the degree to which freedom of information has been recognized as a human right, and study the possibility of widespread recognition of such a human right in the future. It will also examine the possible benefits of such recognition for the development of the human right to free expression.

Keywords: freedom of information, freedom of expression, human rights, government information

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Authors: William Xiu Shun Wong, Myungsu Lim, Yoonjin Hyun, Chen Liu, Seongi Choi, Dasom Kim, Kee-Young Kwahk, Namgyu Kim

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Recently, many users have begun to frequently share their opinions on diverse issues using various social media. Therefore, numerous governments have attempted to establish or improve national policies according to the public opinions captured from various social media. In this paper, we indicate several limitations of the traditional approaches to analyze public opinion on science and technology and provide an alternative methodology to overcome these limitations. First, we distinguish between the science and technology analysis phase and the social issue analysis phase to reflect the fact that public opinion can be formed only when a certain science and technology is applied to a specific social issue. Next, we successively apply a start list and a stop list to acquire clarified and interesting results. Finally, to identify the most appropriate documents that fit with a given subject, we develop a new logical filter concept that consists of not only mere keywords but also a logical relationship among the keywords. This study then analyzes the possibilities for the practical use of the proposed methodology thorough its application to discover core issues and public opinions from 1,700,886 documents comprising SNS, blogs, news, and discussions.

Keywords: big data, social network analysis, text mining, topic modeling

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Authors: Kateřina Struhařová

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The paper gives the evidence of quality of accounting information of Czech private companies. In general the private companies in the Czech Republic do not see the benefits of providing accounting information of high quality. Based on the research of financial statements of entrepreneurs and companies in Zlin region it was confirmed that the quality of accounting information differs among the private entities and that the major impact on the accounting information quality has the fact if the financial statements are audited as well as the size of the entity. Also the foreign shareholders and lenders have some impact on the accounting information quality.

Keywords: accounting information quality, financial statements, Czech Republic, private companies

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Authors: Mohamed Amin Mekheimer

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This study aimed to investigate the effects of paper-based monolingual, pop-up and type-in electronic dictionaries on improving reading comprehension and incidental vocabulary acquisition and retention in an EFL context. It tapped into how computer-mediated dictionaries may have facilitated/impeded reading comprehension and vocabulary acquisition. Findings showed differential effects produced by the three treatments compared with the control group. Specifically, it revealed that the pop-up dictionary condition had the shortest average vocabulary searching time, vocabulary and text reading time, yet with less than the type-in dictionary group but more than the book dictionary group in terms of frequent dictionary 'look-ups' (p<.0001). In addition, ANOVA analyses also showed that text reading time differed significantly across all four treatments, and so did reading comprehension. Vocabulary acquisition was reported as enhanced in the three treatments rather than in the control group, but still with insignificant differences across the three treatments, yet with more differential effects in favour of the pop-up condition. Data also assert that participants preferred the pop-up e-dictionary more than the type-in and paper-based groups. Explanations of the findings vis-à-vis the cognitive load theory were presented. Pedagogical implications and suggestions for further research were forwarded at the end.

Keywords: computer-mediated dictionaries, type-in dictionaries, pop-up dictionaries, reading comprehension, vocabulary acquisition

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Authors: Zaynab El Khattabi, Youness Tabii, Abdelhamid Benkaddour

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Nowadays, huge amount of multimedia repositories make the browsing, retrieval and delivery of video contents very slow and even difficult tasks. Video summarization has been proposed to improve faster browsing of large video collections and more efficient content indexing and access. In this paper, we focus on approaches to video summarization. The video summaries can be generated in many different forms. However, two fundamentals ways to generate summaries are static and dynamic. We present different techniques for each mode in the literature and describe some features used for generating video summaries. We conclude with perspective for further research.

Keywords: video summarization, static summarization, video skimming, semantic features

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Authors: Sunusi Tijjani

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Information and communication technology is an indispensable tool in the performance of office technology managers. Today's offices are automated and equipped with modern office machines that enhances and improve the work of office managers. However, today's office technology managers can process, evaluate, manage and communicate all forms of information using technological devices. Information and Communication Technology is viewed as the process of processing, storing ad dissemination information while office technology managers are trained professional who can effectively operate modern office machines, perform administrative duties and attend meetings to take dawn minute of meetings. This paper examines the importance of information and communication technology toward enhancing the work of office managers. It also stresses the importance of information and communication technology toward proper and accurate record management.

Keywords: communication, information, technology, managers

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Authors: Haixu Yu, Wenhui Cao

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Tailoring Large Language Models (LLMs) to perform legal reasoning has been a popular trend in the study of AI and law. Researchers have mainly employed two methods to unlock the potential of LLMs, namely by finetuning the LLMs to expand their knowledge of law and by restructuring the prompts (In-Context Learning) to optimize the LLMs’ understanding of the legal questions. Although claiming the finetuning and renovated prompting can make LLMs more competent in legal reasoning, most state-of-the-art studies show quite limited improvements of practicability. In this paper, drawing on the study of the complexity and low interpretability of legal texts, we propose a prompting strategy based on the Chain of Thought (CoT) method. Instead of merely instructing the LLM to reason “step by step”, the prompting strategy requires the tested LLM to identify the ambiguity in the questions as the first step and then allows the LLM to generate corresponding answers in line with different understandings of the identified terms as the following step. The proposed prompting strategy attempts to encourage LLMs to "interpret" the given text from various aspects. Experiments that require the LLMs to answer “case analysis” questions of bar examination with general LLMs such as GPT 4 and legal LLMs such as LawGPT show that the prompting strategy can improve LLMs’ ability to better understand complex legal texts.

Keywords: ambiguity-identification, prompt, large language model, legal text understanding

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Authors: Owen Harrington-Fernandez, Pilar Alderete-Diez

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Up until recently, translation studies treated children’s literature as something of a marginal preoccupation, but the recent attention that this text type has attracted suggests that it may be fertile ground for research. This paper contributes to this new research avenue by applying a sociolinguistic theoretical framework to explore issues around the intersubjective co-construction of identity in the American English translation of the Spanish children’s story, Manolito Gafotas. The application of Bucholtz and Hall’s framework achieves two objectives: (1) it identifies shifts in the translation of the main character’s behaviour as culturally and morally motivated manipulations, and (2) it demonstrates how the context of translation becomes the very censorship machine that delegitimises the identity of the main character, and, concomitantly, the identity of the implied reader(s). If we take identity to be an intersubjective phenomenon, then it logicall follows that expurgating the identity of the main character necessarily shifts the identity of the implied reader(s) also. It is a double censorship of identity carried out under the auspices of an intellectual colonisation of a Spanish text. After reporting on the results of the analysis, the paper ends by raising the question of censorship in translation, and, more specifically, in children’s literature, in order to promote debate around this topic.

Keywords: censorship, identity, sociolinguistics, translation

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Authors: Vivien Chee Pei Wei

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Today we live in a scenario in which letters share space with images on screens that vary in size, shape, and style. The popularization of television, then the computer and now the e-readers, tablets, and smartphones made the electronic assume the role that previously was restricted to printed materials. Since the extensive use of new technologies to produce, disseminate, collect and access electronic publications began, the changes to reading has been intensified. To be able to read online, it involves more than just utilizing specific skills, strategies, and practices, but also in negotiating multiple information sources. In this study, different perspectives of digital reading are being explored in order to define the key aspects of the term. The focus is to explore how new technologies affect how undergraduates’ reading behavior, which in turn, gives readers different reading levels and engagement with the text and other support materials in the same media. There is also the importance of the relationship between reading platforms, reading levels and formats of electronic publications. The study looks at the online reading practices of about 100 undergraduates from a local university. The data collected using the survey and interviews with the respondents are analyzed thematically. Findings from this study found that both digital and traditional reading are interrelated, and should not be viewed as separate, but complementary to each other. However, reading online complicates some of the skills required by traditional reading. Consequently, in order to successfully read and comprehend multiple sources of information online, undergraduates need regular opportunities to practice and develop their skills as part of their natural reading practices.

Keywords: concepts, digital reading, literacy, traditional reading

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Authors: Veena Rani

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This paper presents the role of academic library in information literacy in the present time. Information is the very important aspect for the growth of any country. In this context information literacy is an essential tool in the development of various fields. Academic library is an essential part of university as well as of an institution. In Academic library we can include university library, college library as well as school library. Academic libraries are playing an important role for information literacy. Academic libraries provide excellent services for the benefit of students, teachers, researchers, and all those who are interested in education. All over the world many of the schemes, policies and services provide for information literacy.

Keywords: information literacy, academic library, tool literacy, higher education

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Authors: Nengi A. H. Ejiobih

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Conflict is one of the defining features of human societies. Often, the use or misuse of language in interaction is the genesis of conflict. As such, it is expected that when people use language they do so in socially determined ways and with almost predictable social effects. The objective of this paper was to examine the interest at work as manifested in language choice and collocations in conflict discourse. It also scrutinized the implications of linguistic features in conflict discourse as it concerns ideology and power relations in political discourse in Nigeria. The methodology used for this paper is an approach from Critical discourse analysis because of its multidisciplinary model of analysis, linguistic features and its implications were analysed. The datum used is a text from the Sunday Sun Newspaper in Nigeria, West Africa titled Akunyili Memo: State of the Nation. Some of the findings include; different ideologies are inherent in conflict discourse, there is the presence of power relations being produced, exercised, maintained and produced throughout the discourse and the use of pronouns in conflict discourse is valuable because it is used to initiate and maintain relationships in social context. This paper has provided evidence that, taking into consideration the nature of the social actions and the way these activities are translated into languages, the meanings people convey by their words are identified by their immediate social, political and historical conditions.

Keywords: conflicts, discourse, language, linguistic features, social context

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Authors: Tobias Milz, L. Macpherson, Varvara Vetrova

Abstract:

The law is a fundamental pillar of human societies as it shapes, controls and governs how humans conduct business, behave and interact with each other. Recent advances in computer-assisted technologies such as NLP, data science and AI are creating opportunities to support the practice, research and study of this pervasive domain. It is therefore not surprising that there has been an increase in investments into supporting technologies for the legal industry (also known as “legal tech” or “law tech”) over the last decade. A sub-discipline of particular appeal is concerned with assisted legal research. Supporting law researchers and practitioners to retrieve information from the vast amount of ever-growing legal documentation is of natural interest to the legal research community. One tool that has been in use for this purpose since the early nineteenth century is legal citation indexing. Among other use cases, they provided an effective means to discover new precedent cases. Nowadays, computer-assisted network analysis tools can allow for new and more efficient ways to reveal the “hidden” information that is conveyed through citation behavior. Unfortunately, access to openly available legal data is still lacking in New Zealand and access to such networks is only commercially available via providers such as LexisNexis. Consequently, there is a need to create, analyze and provide a legal citation network with sufficient data to support legal research tasks. This paper describes the development and analysis of a legal citation Network for New Zealand containing over 300.000 decisions from 125 different courts of all areas of law and jurisdiction. Using python, the authors assembled web crawlers, scrapers and an OCR pipeline to collect and convert court decisions from openly available sources such as NZLII into uniform and machine-readable text. This facilitated the use of regular expressions to identify references to other court decisions from within the decision text. The data was then imported into a graph-based database (Neo4j) with the courts and their respective cases represented as nodes and the extracted citations as links. Furthermore, additional links between courts of connected cases were added to indicate an indirect citation between the courts. Neo4j, as a graph-based database, allows efficient querying and use of network algorithms such as PageRank to reveal the most influential/most cited courts and court decisions over time. This paper shows that the in-degree distribution of the New Zealand legal citation network resembles a power-law distribution, which indicates a possible scale-free behavior of the network. This is in line with findings of the respective citation networks of the U.S. Supreme Court, Austria and Germany. The authors of this paper provide the database as an openly available data source to support further legal research. The decision texts can be exported from the database to be used for NLP-related legal research, while the network can be used for in-depth analysis. For example, users of the database can specify the network algorithms and metrics to only include specific courts to filter the results to the area of law of interest.

Keywords: case citation network, citation analysis, network analysis, Neo4j

Procedia PDF Downloads 101

Authors: Stefan Bauer, Josef Frysak

Abstract:

According to the scientific information management literature, the improper use of information technology (e.g. personal computers) by employees are one main cause for operational and information security loss events. Therefore, organizations implement information security awareness programs to increase employees’ awareness to further prevention of loss events. However, in many cases these information security awareness programs consist of conventional delivery methods like posters, leaflets, or internal messages to make employees aware of information security policies. We assume that a viral information security awareness video might be more effective medium than conventional methods commonly used by organizations. The purpose of this research is to develop a viral video artifact to improve employee security behavior concerning information technology.

Keywords: information security awareness, delivery methods, viral videos, employee security behavior

Procedia PDF Downloads 540