Search results for: short text analysis

Authors: Beier Zhu, Rui Zhang, Qi Song

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Text contained within fixed-layout documents can be of great semantic value and so requires a high localization accuracy, such as ID cards, invoices, cheques, and passports. Recently, algorithms based on deep convolutional networks achieve high performance on text detection tasks. However, for text localization in fixed-layout documents, such algorithms detect word bounding boxes individually, which ignores the layout information. This paper presents a novel architecture built on convolutional neural networks (CNNs). A global text localization network and a regional bounding-box regression network are introduced to tackle the problem in a coarse-to-fine manner. The text localization network simultaneously locates word bounding points, which takes the layout information into account. The bounding-box regression network inputs the features pooled from arbitrarily sized RoIs and refine the localizations. These two networks share their convolutional features and are trained jointly. A typical type of fixed-layout documents: ID cards, is selected to evaluate the effectiveness of the proposed system. These networks are trained on data cropped from nature scene images, and synthetic data produced by a synthetic text generation engine. Experiments show that our approach locates high accuracy word bounding boxes and achieves state-of-the-art performance.

Keywords: bounding box regression, convolutional networks, fixed-layout documents, text localization

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Authors: Yu Zhang, Pedro Desouza

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Since big data has become substantially more accessible and manageable due to the development of powerful tools for dealing with unstructured data, people are eager to mine information from social media resources that could not be handled in the past. Sentiment analysis, as a novel branch of text mining, has in the last decade become increasingly important in marketing analysis, customer risk prediction and other fields. Scientists and researchers have undertaken significant work in creating and improving their sentiment models. In this paper, we present a concept of selecting appropriate classifiers based on the features and qualities of data sources by comparing the performances of five classifiers with three popular social media data sources: Twitter, Amazon Customer Reviews, and Movie Reviews. We introduced a couple of innovative models that outperform traditional sentiment classifiers for these data sources, and provide insights on how to further improve the predictive power of sentiment analysis. The modelling and testing work was done in R and Greenplum in-database analytic tools.

Keywords: sentiment analysis, social media, Twitter, Amazon, data mining, machine learning, text mining

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Authors: García López

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The Government Departments of Health have the task of informing and educating citizens about public health issues. For this, they use channels like Twitter, key in the search for health information and the propagation of content. The tweets, important in the virality of the content, may contain emotions that influence the contagion and exchange of knowledge. The goal of this study is to perform an analysis of the emotional projection of health information shared on Twitter by official American accounts: the disease control account CDCgov, National Institutes of Health, NIH, the government agency HHSGov, and the professional organization PublicHealth. For this, we used Tone Analyzer, an International Business Machines Corporation (IBM) tool specialized in emotion detection in text, corresponding to the categorical model of emotion representation. For 15 days, all tweets from these accounts were analyzed with the emotional analysis tool in text. The results showed that their tweets contain an important emotional load, a determining factor in the success of their communications. This exposes that official accounts also use subjective language and contain emotions. The predominance of emotion joy over sadness and the strong presence of emotions in their tweets stimulate the virality of content, a key in the work of informing that government health departments have.

Keywords: emotions in tweets, emotion detection in the text, health information on Twitter, American health official accounts, emotions on Twitter, emotions and content

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

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The amount of real-time data generated through various mass media has been increasing rapidly. In this study, we had performed topic analysis by using the unstructured text data that is distributed through news article. As one of the most prevalent applications of topic analysis, the issue tracking technique investigates the changes of the social issues that identified through topic analysis. Currently, traditional issue tracking is conducted by identifying the main topics of documents that cover an entire period at the same time and analyzing the occurrence of each topic by the period of occurrence. However, this traditional issue tracking approach has limitation that it cannot discover dynamic mutation process of complex social issues. The purpose of this study is to overcome the limitations of the existing issue tracking method. We first derived core issues of each period, and then discover the dynamic mutation process of various issues. In this study, we further analyze the mutation process from the perspective of the issues categories, in order to figure out the pattern of issue flow, including the frequency and reliability of the pattern. In other words, this study allows us to understand the components of the complex issues by tracking the dynamic history of issues. This methodology can facilitate a clearer understanding of complex social phenomena by providing mutation history and related category information of the phenomena.

Keywords: Data Mining, Issue Tracking, Text Mining, topic Analysis, topic Detection, Trend Detection

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Authors: Bussabamintra Chalauisaeng

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The creative writing skill of Thai fourth year university learners majoring in English at Khon Kaen University, Thailand has been enhanced in an English creative writing course through the implementation of creative thinking process. The creative writing assignments cover writing a variety of short poems and a short story, bibliography and short play scripts. However, this study focuses mainly on writing short poems and short stories through the implementation of creative thinking process via action research design with on-going needs analysis and feedbacks to meet their learning needs for 45 hours. At the end of the course, forty two learners’ creative writing skill appeared to be significantly improved. Through the research instruments such as the tasks assigned both inside and outside the class as self –study including class observation, semi-conversational interviews and teacher feedback both in persons and on line including peer feedbacks. The research findings show that the target learners could produce better short poems and short story assessed by the set of criteria such as the creative and innovative short poems and short stories with complete and interesting elements of a short story like plot, theme, setting, symbolism and so on. This includes a higher level of the awareness of the pragmatic use of English writing in terms of word choices, grammar rules and writing styles. All of these outcomes reflect positive trends of success in terms of the learners’ improved creative writing skill as well as better attitudes to and motivation for learning to write English for pleasure. More interestingly, many learners claimed that this innovative teaching method through the implementation of creative thinking process integrated with creative writing help stretch their imaginations and inspire them to become a writer in the future.

Keywords: creative thinking process, creative writing skill, enhancing, implementing

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Authors: Eny Syatriana, Ardiansyah

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The purpose of recent study was to develop a learning model on writing, based on the reading texts which will be read by the students using reflection strategy. The strategy would allow the students to read the text and then they would write back the main idea and to develop the text by using their own sentences. So, the writing practice was begun by reading an interesting text, then the students would develop the text which has been read into their writing. The problem questions are (1) what kind of learning model that can develop the students writing ability? (2) what is the achievement of the students of STKIP YPUP through reflection strategy? (3) is the using of the strategy effective to develop students competence In writing? (4) in what level are the students interest toward the using of a strategy In writing subject? This development research consisted of some steps, they are (1) need analysis (2) model design (3) implementation (4) model evaluation. The need analysis was applied through discussion among the writing lecturers to create a learning model for writing subject. To see the effectiveness of the model, an experiment would be delivered for one class. The instrument and learning material would be validated by the experts. In every steps of material development, there was a learning process, where would be validated by an expert. The research used development design. These Principles and procedures or research design and development .This study, researcher would do need analysis, creating prototype, content validation, and limited empiric experiment to the sample. In each steps, there should be an assessment and revision to the drafts before continue to the next steps. The second year, the prototype would be tested empirically to four classes in STKIP YPUP for English department. Implementing the test greatly was done through the action research and followed by evaluation and validation from the experts.

Keywords: learning model, reflection, strategy, reading, writing, development

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Authors: Albina Vodyanitskaya

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Given the culture- and language-specific nature of evaluation, this phenomenon is widely studied around the linguistic world and may be regarded as a challenge for translators. Evaluation penetrates all the levels of a scientific text, influences its composition and the reader’s attitude towards the information presented. One of the most challenging and rarely studied phenomena is the individual style of the scientific writer, which is mostly reflected in the use of evaluative language means. The evaluative and expressive potential of a scientific text is becoming more and more welcoming area for researchers, which stems in the shift towards anthropocentric paradigm in linguistics. Other reasons include: the cognitive and psycholinguistic processes that accompany knowledge acquisition, a genre-determined nature of a scientific text, the increasing public concern about the quality of scientific papers and some such. One more important issue, is the fact that linguists all over the world still argue about the definition of evaluation and its functions in the text. The author analyzes various approaches towards the study of evaluation and scientific texts. A comparative analysis of English and Russian dissertations and other scientific papers with regard to evaluative language means reveals major differences and similarities between English and Russian scientific style. Though standardized and genre-specific, English scientific texts contain more figurative and expressive evaluative means than the Russian ones, which should be taken into account while translating scientific papers. The processes that evaluation undergoes while being expressed by means of a target language are also analyzed. The author offers a target-language-dependent strategy for the translation of evaluation in English and Russian scientific texts. The findings may contribute to the theory and practice of translation and can increase scientific writers’ awareness of inter-language and intercultural differences in evaluative language means.

Keywords: academic discourse, evaluation, scientific text, scientific writing, translation

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Authors: Rabi Mouhcine, Amrouch Mustapha, Mahani Zouhir, Mammass Driss

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In this paper, we present a system for offline recognition cursive Arabic handwritten text based on Hidden Markov Models (HMMs). The system is analytical without explicit segmentation used embedded training to perform and enhance the character models. Extraction features preceded by baseline estimation are statistical and geometric to integrate both the peculiarities of the text and the pixel distribution characteristics in the word image. These features are modelled using hidden Markov models and trained by embedded training. The experiments on images of the benchmark IFN/ENIT database show that the proposed system improves recognition.

Keywords: recognition, handwriting, Arabic text, HMMs, embedded training

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Authors: José Antonio Núñez

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Sigmund Freud’s Theory of Psychoanalysis was a groundbreaking contribution to the province of the human psyche and behavior. Nowadays, psychoanalytic theory is applied to numerous fields. One of them is literature. Literary criticism has put into practice the basis of Freud’s idea to analyze literary works. This essay is about the analysis of Edgar A. Poe’s short story ‘The Tell-Tale Heart,’ under the lens of Freud’s psychoanalytical perspective. In 1919, it was published ‘Das Unheimliche’ (The Uncanny) by Freud. On this article, the famous Austrian psychoanalyst showed his explanations about what he called ‘the uncanny,’ and its relation to the human unconscious. In this paper, Freud’s famous article has been used to analyze Poe’s short story ‘The Tell-Tale Heart,’ and to find the analogies that exist between Poe’s macabre short story and Freud’s theory of ‘the uncanny.’

Keywords: psychoanalysis, theory of the unconscious, the uncanny, unheimlich

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Authors: Moustapha H. Ibrahim, Dahir Abdourahman

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This document presents a short-circuit fault detection process in a photovoltaic (PV) system. The proposed method is developed in MATLAB/Simulink. It determines whatever the size of the installation number of the short circuit module. The proposed algorithm indicates the presence or absence of an abnormality on the power of the PV system through measures of hourly global irradiation, power output, and ambient temperature. In case a fault is detected, it displays the number of modules in a short circuit. This fault detection method has been successfully tested on two different PV installations.

Keywords: PV system, short-circuit, fault detection, modelling, MATLAB-Simulink

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Authors: Ming Liu, Chong Wu, Bingquan Liu, Lei Chen

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Internet users have to face the massive amount of textual data every day. Organizing texts into categories can help users dig the useful information from large-scale text collection. Clustering, in fact, is one of the most promising tools for categorizing texts due to its unsupervised characteristic. Unfortunately, most of traditional clustering algorithms lose their high qualities on large-scale text collection. This situation mainly attributes to the high- dimensional vectors generated from texts. To effectively and efficiently cluster large-scale text collection, this paper proposes a vector reconstruction based clustering algorithm. Only the features that can represent the cluster are preserved in cluster’s representative vector. This algorithm alternately repeats two sub-processes until it converges. One process is partial tuning sub-process, where feature’s weight is fine-tuned by iterative process. To accelerate clustering velocity, an intersection based similarity measurement and its corresponding neuron adjustment function are proposed and implemented in this sub-process. The other process is overall tuning sub-process, where the features are reallocated among different clusters. In this sub-process, the features useless to represent the cluster are removed from cluster’s representative vector. Experimental results on the three text collections (including two small-scale and one large-scale text collections) demonstrate that our algorithm obtains high quality on both small-scale and large-scale text collections.

Keywords: vector reconstruction, large-scale text clustering, partial tuning sub-process, overall tuning sub-process

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Authors: Rim Messaoudi, Nogaye-Gueye Gning, François Azelart

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Automatic text classification applies mostly natural language processing (NLP) and other AI-guided techniques to automatically classify text in a faster and more accurate manner. This paper discusses the subject of using predictive maintenance to manage incident tickets inside the sociality. It focuses on proposing a tool that treats and analyses comments and notes written by administrators after resolving an incident ticket. The goal here is to increase the quality of these comments. Additionally, this tool is based on NLP and machine learning techniques to realize the textual analytics of the extracted data. This approach was tested using real data taken from the French National Railways (SNCF) company and was given a high-quality result.

Keywords: machine learning, text classification, NLP techniques, semantic representation

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Authors: Paolo Fantozzi, Luigi Laura, Umberto Nanni

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The problem of Entity relation discovery in structured data, a well covered topic in literature, consists in searching within unstructured sources (typically, text) in order to find connections among entities. These can be a whole dictionary, or a specific collection of named items. In many cases machine learning and/or text mining techniques are used for this goal. These approaches might be unfeasible in computationally challenging problems, such as processing massive data streams. A faster approach consists in collecting the cooccurrences of any two words (entities) in order to create a graph of relations - a cooccurrence graph. Indeed each cooccurrence highlights some grade of semantic correlation between the words because it is more common to have related words close each other than having them in the opposite sides of the text. Some authors have used sliding windows for such problem: they count all the occurrences within a sliding windows running over the whole text. In this paper we generalise such technique, coming up to a Weighted-Distance Sliding Window, where each occurrence of two named items within the window is accounted with a weight depending on the distance between items: a closer distance implies a stronger evidence of a relationship. We develop an experiment in order to support this intuition, by applying this technique to a data set consisting in the text of the Bible, split into verses.

Keywords: cooccurrence graph, entity relation graph, unstructured text, weighted distance

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Authors: Aishwarya Talapuru, Sri Silpa Padmanabhuni, B. Jyoshna

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Cryptography helps in preventing threats to information security by providing various algorithms. This study introduces a new symmetric key encryption algorithm for information security which is linked with the "raagas" which means Indian traditional scale and pattern of music notes. This algorithm takes the plain text as input and starts its encryption process. The algorithm then randomly selects a raaga from the list of raagas that is assumed to be present with both sender and the receiver. The plain text is associated with the thus selected raaga and an intermediate cipher-text is formed as the algorithm converts the plain text characters into other characters, depending upon the rules of the algorithm. This intermediate code or cipher text is arranged in various patterns in three different rounds of encryption performed. The total number of rounds in the algorithm is equal to the multiples of 3. To be more specific, the outcome or output of the sequence of first three rounds is again passed as the input to this sequence of rounds recursively, till the total number of rounds of encryption is performed. The raaga selected by the algorithm and the number of rounds performed will be specified at an arbitrary location in the key, in addition to important information regarding the rounds of encryption, embedded in the key which is known by the sender and interpreted only by the receiver, thereby making the algorithm hack proof. The key can be constructed of any number of bits without any restriction to the size. A software application is also developed to demonstrate this process of encryption, which dynamically takes the plain text as input and readily generates the cipher text as output. Therefore, this algorithm stands as one of the strongest tools for information security.

Keywords: cipher text, cryptography, plaintext, raaga

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Authors: O. Behar, A. Khellaf, K. Mohammedi, S. Ait Kaci

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Up to now, most validation studies have been based on the MBE and RMSE, and therefore, focused only on long and short terms performance to test and classify solar radiation models. This traditional analysis does not take into account the quality of modeling and linearity. In our analysis we have tested 22 solar radiation models that are capable to provide instantaneous direct and global radiation at any given location Worldwide. We introduce a new indicator, which we named Global Accuracy Indicator (GAI) to examine the linear relationship between the measured and predicted values and the quality of modeling in addition to long and short terms performance. Note that the quality of model has been represented by the T-Statistical test, the model linearity has been given by the correlation coefficient and the long and short term performance have been respectively known by the MBE and RMSE. An important founding of this research is that the use GAI allows avoiding default validation when using traditional methodology that might results in erroneous prediction of solar power conversion systems performances.

Keywords: solar radiation model, parametric model, performance analysis, Global Accuracy Indicator (GAI)

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Authors: Shatha Khuzaee

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The study develops multimodal stylistic approach to analyse a number of BBC online news articles reporting some key events from the so called ‘Arab Uprisings’. Critical stylistics (CS) and visual grammar (VG) provide insightful arguments to the ways ideology is projected through different verbal and visual modes, yet they are mode specific because they examine how each mode projects its meaning separately and do not attempt to clarify what happens intersemiotically when the two modes co-occur. Therefore, it is the task undertaken in this research to propose multimodal stylistic approach that addresses the issue of ideology construction when the two modes co-occur. Informed by functional grammar and social semiotics, the analysis attempts to integrate three linguistic models developed in critical stylistics, namely, transitivity choices, prioritizing and hypothesizing along with their visual equivalents adopted from visual grammar to investigate the way ideology is constructed, in multimodal text, when text/image participate and interrelate in the process of meaning making on the textual level of analysis. The analysis provides comprehensive theoretical and analytical elaborations on the different points of integration between CS linguistic models and VG equivalents which operate on the textual level of analysis to better account for ideology construction in news as non-literary multimodal texts. It is argued that the analysis well thought out a plan that would remark the first step towards the integration between the well-established linguistic models of critical stylistics and that of visual analysis to analyse multimodal texts on the textual level. Both approaches are compatible to produce multimodal stylistic approach because they intend to analyse text and image depending on whatever textual evidence is available. This supports the analysis maintain the rigor and replicability needed for a stylistic analysis like the one undertaken in this study.

Keywords: multimodality, stylistics, visual grammar, social semiotics, functional grammar

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Authors: Teguh Sugiarto, Ahmad Subagyo, Ludiro Madu, Amir Mohammadian Amiri

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Recently, the significant fluctuations accosiated with Indonesian economy justifies the need for paying more attention to this issue. In this regard, the main objective of this study is to investigate the relationship between two issues related to the macro Indonesia economy called consumption and GDP during the period of 1967 to 2014. This research method exploits short term and long term relationships using Granger and subsequently, models them by the causality method . However, using analysis of Granger with Johansen shows that there is not only a long term, but also a short-long relationship between GDP and consumption using lags the interval 5.

Keywords: cointegration, Granger causality, GDP, consumption

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Authors: Hamda Ajmal, Karen Young, Ruth Melia, John Bogue, Mary O'Sullivan, Jim Duggan, Hannah Wood

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The Covid-19 pandemic led to a range of public health mitigation strategies in order to suppress the SARS-CoV-2 virus. The drastic changes in everyday life due to lockdowns had the potential for a significant negative impact on public mental health, and a key public health goal is to now assess the evidence from available Irish datasets to provide useful insights on this issue. Text-50808 is an online text-based mental health support service, established in Ireland in 2020, and can provide a measure of revealed distress and mental health concerns across the population. The aim of this study is to explore statistical associations between public mental health in Ireland and the Covid-19 pandemic. Uniquely, this study combines two measures of emotional wellbeing in Ireland: (1) weekly text volume at Text-50808, and (2) emotional wellbeing indicators reported by respondents of the Amárach public opinion survey, carried out on behalf of the Department of Health, Ireland. For this analysis, a multivariate graphical exploratory data analysis (EDA) was performed on the Text-50808 dataset dated from 15th June 2020 to 30th June 2021. This was followed by time-series analysis of key mental health indicators including: (1) the percentage of daily/weekly texts at Text-50808 that mention Covid-19 related issues; (2) the weekly percentage of people experiencing anxiety, boredom, enjoyment, happiness, worry, fear and stress in Amárach survey; and Covid-19 related factors: (3) daily new Covid-19 case numbers; (4) daily stringency index capturing the effect of government non-pharmaceutical interventions (NPIs) in Ireland. The cross-correlation function was applied to measure the relationship between the different time series. EDA of the Text-50808 dataset reveals significant peaks in the volume of texts on days prior to level 3 lockdown and level 5 lockdown in October 2020, and full level 5 lockdown in December 2020. A significantly high positive correlation was observed between the percentage of texts at Text-50808 that reported Covid-19 related issues and the percentage of respondents experiencing anxiety, worry and boredom (at a lag of 1 week) in Amárach survey data. There is a significant negative correlation between percentage of texts with Covid-19 related issues and percentage of respondents experiencing happiness in Amárach survey. Daily percentage of texts at Text-50808 that reported Covid-19 related issues to have a weak positive correlation with daily new Covid-19 cases in Ireland at a lag of 10 days and with daily stringency index of NPIs in Ireland at a lag of 2 days. The sudden peaks in text volume at Text-50808 immediately prior to new restrictions in Ireland indicate an association between a rise in mental health concerns following the announcement of new restrictions. There is also a high correlation between emotional wellbeing variables in the Amárach dataset and the number of weekly texts at Text-50808, and this confirms that Text-50808 reflects overall public sentiment. This analysis confirms the benefits of the texting service as a community surveillance tool for mental health in the population. This initial EDA will be extended to use multivariate modeling to predict the effect of additional Covid-19 related factors on public mental health in Ireland.

Keywords: COVID-19 pandemic, data analysis, digital health, mental health, public health, digital health

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Authors: Kalyani Gandhi

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The eighteenth century in Britain saw a great burst of activity in writing (letters, journals, newspapers, essays); often these modes of writing had a public-spirited bent in-step with the prevailing intellectual atmosphere. Mary Wollstonecraft was one of the leading intellectuals of that period who utilized letter writing to convey her thoughts on the exciting political developments of the late eighteenth century. Fusing together her anxieties and concerns about humanity in general and herself in particular, Wollstonecraft’s views of the world around her are filtered through the lens of her subjectivity. Thus, Wollstonecraft’s letters covered a wide range of topics on both the personal and political level (for the two are often entwined in Wollstonecraft’s characteristic style of analysis) such as sentiment, gender, nature, peasantry, the class system, the legal system, political duties and rights of both rulers and subjects, death, immortality, religion, family and education. Therefore, this paper intends to examine the manner in which Wollstonecraft utilizes letter-writing to constitute and develop Romantic self-hood, understand the world around her and illustrate her ideas on the political and social happenings in Europe. The primary text analyzed will be Mary Wollstonecraft's Letters Written During a Short Stay in Sweden, Denmark and Norway (1796) and the analysis of this text will be supplemented by researching 18th-century British letter writing culture, with a special emphasis on the epistolary habits of women. Within this larger framework, this paper intends to examine the manner in which this hybrid of travel and epistolary writing aided Mary Wollstonecraft's expression on Romantic selfhood and how it was complicated by ideas of gender. This paper reveals Wollstonecraft's text to be wrought with anxiety about the world around her and within her; thus, the personal-public nature of the epistolary format particularly suits her characteristic point of view that looks within and without. That is to say, Wollstonecraft’s anxieties about gender and self, are as much about the women she sees in the world around her as much as they are about her young daughter and herself. Wollstonecraft constantly explores and examines this anxiety within the different but interconnected realms of politics, economics, history and society. In fact, it is her complex technique of entwining these aforementioned concerns with a closer look at interpersonal relationships among men and women (she often mentions specific anecdotes and instances) that make Wollstonecraft's Letters so engaging and insightful. Thus, Wollstonecraft’s Letters is an exemplar of British Romantic writing due to the manner in which it explores the bond between the individual and society. Mary Wollstonecraft's nuances this exploration by incorporating her concerns about women and the playing out of gender in society. Thus, Wollstonecraft’s Letters is an invaluable contribution to the field of British Romanticism, particularly as it offers crucial insight on female Romantic writing that can broaden and enrich the current academic understanding of the field.

Keywords: British romanticism, letters, feminism, travel writing

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Authors: I. Pina, M. Painho

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Increased knowledge about the nature of place and the conditions under which space becomes place is a key factor for better urban planning and place-making. Although there is a broad consensus on the relevance of this knowledge, difficulties remain in relating the theoretical framework about place and urban management. Issues related to representation of places are among the greatest obstacles to overcome this gap. With this critical discussion, based on literature review, we intended to explore, in a common framework for geographical analysis, the potential of stories to spell out place meanings, bringing together qualitative text analysis and text mining in order to capture and represent the singularity contained in each person's life history, and the patterns of social processes that shape places. The development of this reasoning is based on the extensive geographical thought about place, and in the theoretical advances in the field of Geographic Information Science (GISc).

Keywords: discourse analysis, geographic information science place, place-making, stories

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Authors: Hyung Jun Ahn

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With the growing importance of social media, it is imperative to analyze it to understand the users. Users share useful information and their experience through social media, where much of what is shared is in the form of texts. This study focused on blogs and aimed to test whether the psycho-linguistic characteristics of blog texts vary with the subject or the type of experience of the texts. For this goal, blog texts about four different types of experience, Go, skiing, reading, and musical were collected through the search API of the Tistory blog service. The analysis of the texts showed that various psycholinguistic characteristics of the texts are different across the four categories of the texts. Moreover, the machine learning experiment using the characteristics for automatic text classification showed significant performance. Specifically, the ensemble method, based on functional tree and bagging appeared to be most effective in classification.

Keywords: blog, social media, text analysis, psycholinguistics

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Authors: Amirreza Karami, Hawraa Nafea Hameed Alzouwain, Freddie A. Bowles

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This study investigates the effects of watching text-relevant video segments with/without subtitles on vocabulary development of Arabic as a Foreign Language (AFL) learners. The participants of the study were assigned to two groups: one control group and one experimental group. The control group received no video-based instruction while the experimental group watched a text-relevant video segment in three stages: pre, while, and post-instruction. The preliminary results of the pre-test and post-test show that watching text-relevant video segments through following a pre-while-post procedure can help the vocabulary development of AFL learners more than non-video-based instruction.

Keywords: text-relevant video segments, vocabulary development, Arabic as a Foreign Language, AFL, pre-while-post instruction

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Authors: K. Sridhar Reddy, M. Amaranatha Reddy, Nilanjan Mitra

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Short paneled concrete pavement (SPCP) with shorter panel size can be an alternative to the conventional jointed plain concrete pavements (JPCP) at the same cost as the asphalt pavements with all the advantages of concrete pavement with reduced thickness, less chance of mid-slab cracking and or dowel bar locking so common in JPCP. Cast-in-situ short concrete panels (short slabs) laid on a strong foundation consisting of a dry lean concrete base (DLC), and cement treated subbase (CTSB) will reduce the thickness of the concrete slab to the order of 180 mm to 220 mm, whereas JPCP was with 280 mm for the same traffic. During the construction of SPCP test sections on two Indian National Highways (NH), it was observed that the joints remain uncracked after a year of traffic. The undoweled and uncracked joints load transfer variability and joint behavior are of interest with anticipation on its long-term performance of the SPCP. To investigate the effects of undoweled and uncracked joints on short slabs, the present study was conducted. A multilayer linear elastic analysis using 3D finite element package for different panel sizes with different thicknesses resting on different types of solid elastic foundation with and without temperature gradient was developed. Surface deflections were obtained from 3D FE model and validated with measured field deflections from falling weight deflectometer (FWD) test. Stress analysis indicates that flexural stresses in short slabs are decreased with a decrease in panel size and increase in thickness. Detailed evaluation of stress analysis with the effects of curling behavior, the stiffness of the base layer and a variable degree of load transfer, is underway.

Keywords: joint behavior, short slabs, uncracked joints, undoweled joints, 3D numerical simulation

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Authors: Yi Gu

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The Three-Body Problem by Cixin Liu has been a bestseller Chinese Sci-Fi novel for years since 2008. The book was translated into English by Ken Liu in 2014 and won the prestigious 2015 science fiction and fantasy writing Hugo Award, drawing greater attention from wider international communities. The story exposes the horrors of the Chinese Cultural Revolution in the 1960s, in an intriguing narrative for readers at home and abroad. However, without the access to the source text, western readers may not be aware that the original Chinese version of the book is rich in gender-bias. Some Chinese scholars have applied feminist translation theories to their analysis on this book before, based on isolated selected, cherry-picking examples. Thus this paper aims to obtain a more thorough picture of how translators can cope with gender discrimination and reshape the gendered discourse from the source text, by systematically investigating the lexical and syntactic patterns in the translation of Liu’s entire book of 400 pages. The source text and the translation were downloaded into digital files, automatically aligned at paragraph level and then manually post-edited. They were then compiled into a parallel corpus of 114,629 English words and 204,145 Chinese characters using Sketch Engine. Gender-discrimination markers such as the overuse of ‘girl’ to describe an adult woman were searched in the source text, and the alignment made it possible to identify the strategies adopted by the translator to mitigate gender discrimination. The results provide a framework for translators to address gender bias. The study also shows how corpus methods can be used to further research in feminist translation and critical discourse analysis.

Keywords: corpus, discourse analysis, feminist translation, science fiction translation

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Authors: Fatima Al-Aswadi, Chan Yong

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With the large volume of unstructured data that increases day by day on the web, the motivation of representing the knowledge in this data in the machine processable form is increased. Ontology is one of the major cornerstones of representing the information in a more meaningful way on the semantic Web. The goal of Ontology learning from text is to elicit and represent domain knowledge in the machine readable form. This paper aims to give a follow-up review on the ontology learning systems from text and some of their defects. Furthermore, it discusses how far the ontology learning process will enhance in the future.

Keywords: concept discovery, deep learning, ontology learning, semantic relation, semantic web

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Authors: Thirayu Jumsai Na Ayudhya

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The attempt to understand about what architecture means to people as they go about their everyday life revealed that knowledge such as environmental psychology, environmental perception, environmental aesthetics, inadequately address the contextualized and holistic theoretical framework. In my previous research, it was found that people’s making senses of their everyday architecture can be addressed in terms of four super‐ordinate themes; (1) building in urban (text), (2) building in (text), (3) building in human (text), (4) and building in time (text). In this research, Bangkok CBD was selected as the focal urban context that the integrated style of architecture is noticeable. It is expected that in a unique urban context like Bangkok CBD unprecedented super-ordinate themes will be unveiled through the reflection of people’s everyday experiences. In this research, people’s architectural experience conducted in Bangkok CBD, Thailand, will be presented succinctly. The research addresses the question of how do people make sense of their everyday architecture/buildings especially in a unique urban context, Bangkok CBD, and identifies ways in which people make sense of their everyday architecture. Two key methodologies are adopted. First, Participant-Produced-Photograph (PPP) allows people to express their experiences of the everyday urban context freely without any interference or forced-data generating by researchers. Second, Interpretative Phenomenological Analysis (IPA) are also applied as main methodologies. With IPA methodology, a small pool of participants is considered giving the detailed level of analysis and its potential to produce a meaningful outcome.

Keywords: architectural experience, building appreciation, design psychology, environmental psychology, sense-making, the everyday experience, transactional theory

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Authors: Mehrnoosh Pirhayati

Abstract:

In this study, the researcher tried to propose a model of Translation Criticism (TC) regarding the phenomenon of Translation Quality Assessment (TQA). With changing the general view on re/writing as an illegal act, the researcher defined a scale for the act of translation and determined the redline of translation with other products. This research attempts to show TC as a related phenomenon to TQA. This study shows that TQA with using the rules and factors of TC as depicted in both product-oriented analysis and process-oriented analysis, determines the orientation or the level of the quality of translation. This study also depicts that TC, regarding TQA’s perspective, reveals the aim of the translation of original text and the root of ideological manipulation and re/writing. On the other hand, this study stresses the existence of a direct relationship between the linguistic materials and semiotic codes of a text or book. This study can be fruitful for translators, scholars, translation criticizers, and translation quality assessors, and also it is applicable in the area of pedagogy.

Keywords: a model of translation criticism, a model of translation quality assessment, critical discourse analysis (CDA), re/writing, translation criticism (TC), translation quality assessment (TQA)

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Authors: Ahmed Abdullah Ahmed

Abstract:

The task of recognizing the writer of a handwritten text has been an attractive research problem in the document analysis and recognition community with applications in handwriting forensics, paleography, document examination and handwriting recognition. This research presents an automatic method for writer recognition from digitized images of unconstrained writings. Although a great effort has been made by previous studies to come out with various methods, their performances, especially in terms of accuracy, are fallen short, and room for improvements is still wide open. The proposed technique employs optimal codebook based writer characterization where each writing sample is represented by a set of features computed from two codebooks, beginning and ending. Unlike most of the classical codebook based approaches which segment the writing into graphemes, this study is based on fragmenting a particular area of writing which are beginning and ending strokes. The proposed method starting with contour detection to extract significant information from the handwriting and the curve fragmentation is then employed to categorize the handwriting into Beginning and Ending zones into small fragments. The similar fragments of beginning strokes are grouped together to create Beginning cluster, and similarly, the ending strokes are grouped to create the ending cluster. These two clusters lead to the development of two codebooks (beginning and ending) by choosing the center of every similar fragments group. Writings under study are then represented by computing the probability of occurrence of codebook patterns. The probability distribution is used to characterize each writer. Two writings are then compared by computing distances between their respective probability distribution. The evaluations carried out on ICFHR standard dataset of 206 writers using Beginning and Ending codebooks separately. Finally, the Ending codebook achieved the highest identification rate of 98.23%, which is the best result so far on ICFHR dataset.

Keywords: off-line text-independent writer identification, feature extraction, codebook, fragments

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Authors: Eunjung Lee

Abstract:

This research investigates the intricate connection between cultural differences and online consumer behaviors by integrating Hofstede's Cultural Dimensions theory with analysis methodologies such as text mining, data mining, and topic analysis. Our aim is to provide a comprehensive understanding of how national cultural differences influence individuals' behaviors when engaging with online reviews. To ensure the relevance of our investigation, we systematically analyze and interpret the cultural nuances influencing online consumer behaviors, especially in the context of online reviews. By anchoring our research in Hofstede's Cultural Dimensions theory, we seek to offer valuable insights for marketers to tailor their strategies based on the cultural preferences of diverse global consumer bases. In our methodology, we employ advanced text mining techniques to extract insights from a diverse range of online reviews gathered globally for a specific product or service like Netflix. This approach allows us to reveal hidden cultural cues in the language used by consumers from various backgrounds. Complementing text mining, data mining techniques are applied to extract meaningful patterns from online review datasets collected from different countries, aiming to unveil underlying structures and gain a deeper understanding of the impact of cultural differences on online consumer behaviors. The study also integrates topic analysis to identify recurring subjects, sentiments, and opinions within online reviews. Marketers can leverage these insights to inform the development of culturally sensitive strategies, enhance target audience segmentation, and refine messaging approaches aligned with cultural preferences. Anchored in Hofstede's Cultural Dimensions theory, our research employs sophisticated methodologies to delve into the intricate relationship between cultural differences and online consumer behaviors. Applied to specific cultural dimensions, such as individualism vs. collectivism, masculinity vs. femininity, uncertainty avoidance, and long-term vs. short-term orientation, the study uncovers nuanced insights. For example, in exploring individualism vs. collectivism, we examine how reviewers from individualistic cultures prioritize personal experiences while those from collectivistic cultures emphasize communal opinions. Similarly, within masculinity vs. femininity, we investigate whether distinct topics align with cultural notions, such as robust features in masculine cultures and user-friendliness in feminine cultures. Examining information-seeking behaviors under uncertainty avoidance reveals how cultures differ in seeking detailed information or providing succinct reviews based on their comfort with ambiguity. Additionally, in assessing long-term vs. short-term orientation, the research explores how cultural focus on enduring benefits or immediate gratification influences reviews. These concrete examples contribute to the theoretical enhancement of Hofstede's Cultural Dimensions theory, providing a detailed understanding of cultural impacts on online consumer behaviors. As online reviews become increasingly crucial in decision-making, this research not only contributes to the academic understanding of cultural influences but also proposes practical recommendations for enhancing online review systems. Marketers can leverage these findings to design targeted and culturally relevant strategies, ultimately enhancing their global marketing effectiveness and optimizing online review systems for maximum impact.

Keywords: comparative analysis, cultural dimensions, marketing intelligence, national culture, online consumer behavior, text mining

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Authors: Khayriniso Bakhtiyarovna Ganiyeva

Abstract:

The article explores the significance of punctuation in achieving communicative competence. It underscores that effective communication goes beyond simply using punctuation correctly. In the successful completion of a communicative activity, it is important not that the writer correctly uses punctuation marks but that he was able to achieve a goal aimed at expressing a certain meaning. The unanimity of the writer and the reader in the mutual understanding of the text is of primary importance. It should also be taken into account that situational communication provides special informative content and expressiveness of speech. Also, the norms of the situation are determined by the nature of the information in the text, and the punctuation marks expressed in accordance with the norm perform logical-semantic, highlighting expressive-emotional and signaling functions. It is a mistake to classify the signs subject to the norm of the situation as created by the author because they functionally reflect the general stylistic features of different texts. Such signs are among the common signs that are codified only by the semantics and structure of the created text.

Keywords: communicative-pragmatic approach, expressiveness of speech, stylistic features, comparative analysis

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