Deposits of clastic carbonate-dominated (calciclastic) sedimentary slope systems in the rock record have been identified mostly as linearly-consistent carbonate apron deposits, even though most ancient clastic carbonate slope deposits fit the submarine fan systems better. Calciclastic submarine fans are consequently rarely described and are poorly understood. Subsequently, very little is known especially in mud-dominated calciclastic submarine fan systems. Presented in this study are a sedimentological core and petrographic characterisation of samples from eleven boreholes from the Lower Carboniferous of Bowland Basin (Northwest England) that reveals a >250 m thick calciturbidite complex deposited in a calciclastic submarine fan setting. Seven facies are recognised from core and thin section characterisation and are grouped into three carbonate turbidite sequences. They include: 1) Calciturbidites, comprising mostly of highto low-density, wavy-laminated bioclast-rich facies; 2) low-density densite mudstones which are characterised by planar laminated and unlaminated muddominated facies; and 3) Calcidebrites which are muddy or hyper-concentrated debrisflow deposits occurring as poorly-sorted, chaotic, mud-supported floatstones. These

Phd by thesis

With the advent of Web 2.0, people became more eager to express and share their opinions on web regarding day-to-day activities and global issues as well. Evolution of social media has also contributed immensely to these activities, thereby providing us a transparent platform to share views across the world. These electronic Word of Mouth (eWOM) statements expressed on the web are much prevalent in business and service industry to enable customer to share his/her point of view. In the last one and half decades, research communities, academia, public and service industries are working rigorously on sentiment analysis, also known as, opinion mining, to extract and analyze public mood and views. In this regard, this paper presents a rigorous survey on sentiment analysis, which portrays views presented by over one hundred articles published in the last decade regarding necessary tasks, approaches, and applications of sentiment analysis. Several sub-tasks need to be performed for sentiment analysis which in turn can be accomplished using various approaches and techniques. This survey covering published literature during 2002-2015, is organized on the basis of sub-tasks to be performed, machine learning and natural language processing techniques used and applications of sentiment analysis. The paper also presents open issues and along with a summary table of a hundred and sixty-one articles.

A survey on opinion mining and sentiment analysis

В статье дана оценка перспектив развития интеграционных процессов науки и образования в российских вузах.

Стратегия интеграционных процессов в сфере науки и образования

Crowdfunding sites like Kickstarter--where entrepreneurs and artists look to the internet for funding--have quickly risen to prominence. However, we know very little about the factors driving the 'crowd' to take projects to their funding goal. In this paper we explore the factors which lead to successfully funding a crowdfunding project. We study a corpus of 45K crowdfunded projects, analyzing 9M phrases and 59 other variables commonly present on crowdfunding sites. The language used in the project has surprising predictive power accounting for 58.56% of the variance around successful funding. A closer look at the phrases shows they exhibit general persuasion principles. For example, also receive two reflects the principle of Reciprocity and is one of the top predictors of successful funding. We conclude this paper by announcing the release of the predictive phrases along with the control variables as a public dataset, hoping that our work can enable new features on crowdfunding sites--tools to help both backers and project creators make the best use of their time and money.

The language that gets people to give: phrases that predict success on kickstarter

The proliferation of fake news on social media has opened up new directions of research for timely identification and containment of fake news and mitigation of its widespread impact on public opinion. While much of the earlier research was focused on identification of fake news based on its contents or by exploiting users’ engagements with the news on social media, there has been a rising interest in proactive intervention strategies to counter the spread of misinformation and its impact on society. In this survey, we describe the modern-day problem of fake news and, in particular, highlight the technical challenges associated with it. We discuss existing methods and techniques applicable to both identification and mitigation, with a focus on the significant advances in each method and their advantages and limitations. In addition, research has often been limited by the quality of existing datasets and their specific application contexts. To alleviate this problem, we comprehensively compile and summarize characteristic features of available datasets. Furthermore, we outline new directions of research to facilitate future development of effective and interdisciplinary solutions.

Combating Fake News: A Survey on Identification and Mitigation Techniques

Исследование влияния пола и психологических характеристик автора на количественные параметры его текста с использованием программы Linguistic Inquiry and Word Count

Диброва Елена Владимировна, Рыжкова Екатерина Сергеевна КОРПУСНЫЕ ИССЛЕДОВАНИЯ ПИСЬМЕННОЙ РЕЧИ В РЕШЕНИИ ЗАДАЧ СУДЕБНОГО АВТОРОВЕДЕНИЯ Обосновывается необходимость использования специальным образом составленных корпусов текстов при разработке методик проведения идентификационной и диагностической автороведческой экспертизы. Приводится краткий анализ существующих корпусов текстов, используемых для построения методик идентификации и диагностирования личности автора текста. Описывается структура корпуса текстов на русском языке Personality, содержащего метаразметку в виде информации об их авторах, и анализируются возможности его применения для решения задач судебного автороведения. Адрес статьи: www.gramota.net/materials/2/2015/8-1/29.html

http://cyberleninka.ru/article/n/korpusnye-issledovaniya-pismennoy-rechi-v-reshenii-zadach-sudebnogo-avtorovedeniya.pdf

Корпусные исследования письменной речи в решении задач судебного автороведения

Одним из перспективных направлений современных исследований является анализ речи с целью выявления психического состояния и оценки психического здоровья говорящего/пишущего. В последние годы наблюдается повышенный интерес к решению задач подобного рода с привлечением методов и средств компьютерной лингвистики и интеллектуального анализа данных (data mining). Отдельной научной проблемой, далекой от своего решения и, несомненно, требующей консолидации усилий психологов, лингвистов и специалистов по интеллектуальному анализу данных, является проблема диагностирования склонности личности к аутоагрессивному поведению и (суициду как к крайней его форме) на основе лингвистического анализа речи. Эта проблема имеет не только теоретическую, но и очевидную практическую значимость и в последние годы активно изучается лингвистами и психологами. С применением методов natural language processing ученые анализируют тексты (преимущественно англоязычные) суицидентов и строят модели, позволяющие классифицировать текст как принадлежащий или не принадлежащий суициденту, а также выявляют особенности таких текстов. При этом если ранее анализировались преимущественно художественные тексты суицидентов, то в новейших работах ученые исследуют интернет-тексты (блоги, твиты, посты в соцсетях) лиц, совершивших суицид либо выражающих намерение его совершить. Русский язык долгое время оставался на периферии подобных исследований. В статье представлены результаты исследований, направленных на выявление языковых особенностей русскоязычных текстов лиц, совершивших законченный суицид, а также лиц, склонных к аутоагрессивному поведению. В указанных исследованиях применялись методы и приемы корпусной лингвистики, компьютерной лингвистики, статистического анализа. Обозначены перспективы дальнейших исследований.

/pdf/linguistic-features-of-the-russian-texts-of-persons-who-20yuzo3lv9.pdf

Linguistic features of the russian texts of persons who committed suicide and persons with a high risk of autoaggressive behavior

The paper investigates the problem of unconscious formal grammatical parameters of the text which are stably correlated with certain personality traits and can be used in authorship attribution to create a personality profile of the author of the written text. The analysis of the scientific literature suggests that one of these parameters can be speech sequences. The attempt has been made to examine a possible use of part of speech tagging as an attribution parameter of the text using the material of a collected corpus of students’ essays with metatags with the information about the authors. Stable correlations are obtained between the personality traits and part of speech tagging, regression models are obtained that prove to be highly accurate. It should be noted that this kind of approach extensively used by contemporary science should be supplemented with psychological, psycholinguistic and cognitive data in order for the theoretical justification to be obtained.

Литвинова Ольга Александровна

Papers

Исследование влияния пола и психологических характеристик автора на количественные параметры его текста с использованием программы Linguistic Inquiry and Word Count

Корпусные исследования письменной речи в решении задач судебного автороведения

Linguistic features of the russian texts of persons who committed suicide and persons with a high risk of autoaggressive behavior

Частоты встречаемости последовательностей частей речи в тексте и психофизиологические характеристики его автора: корпусное исследование