Сентимент-анализ брендов в российской блогосфере как инструмент маркетинговых исследований
Das Buch ist in mehrer Hinsicht eine Besonderheit: Zunächst erinnert es an den kürzlich verstorbenen Peter Haber, spiritus rector der Idee und Herausgeber posthum gemeinsam mit Eva Pfanzelter, unter Mitarbeit von Julia Schreiner. Zum anderen ist es das erste Buch in der deutschsprachigen Geschichtswissenschaft, das in einem Open Peer Review-Prozess erschienen ist. Zur Erinnerung: vom 10. Oktober bis 10. Dezember 2012 standen 18 Beiträge auf der Oldenbourg-Website zur absatzweisen Kommentierung bereit
This book provides a comprehensive analysis of the ways in which new media technologies have shaped language and communication in contemporary Russia. It traces the development of the Russian-language internet (Runet) from late-Soviet cybernetics to the advent of Twitter and explores the evolution of web-based communication practices, showing how they have both shaped and been shaped by social, political, linguistic and literary realities. Throughout the volume, leading Runet scholars draw attention to features and trends that are characteristic of global new media, as well as those that are more specific to Russian media culture.
The Semantic Evaluation (SemEval) series of workshops focuses on the evaluation and comparison of systems that can analyse diverse semantic phenomena in text with the aim of extending the current state of the art in semantic analysis and creating high quality annotated datasets in a range of increasingly challenging problems in natural language semantics. SemEval provides an exciting forum for researchers to propose challenging research problems in semantics and to build systems/techniques to address such research problems. SemEval-2016 is the tenth workshop in the series of International Workshops on Semantic Evaluation Exercises. The first three workshops, SensEval-1 (1998), SensEval-2 (2001), and SensEval-3 (2004), focused on word sense disambiguation, each time growing in the number of languages offered, in the number of tasks, and also in the number of participating teams. In 2007, the workshop was renamed to SemEval, and the subsequent SemEval workshops evolved to include semantic analysis tasks beyond word sense disambiguation. In 2012, SemEval turned into a yearly event. It currently runs every year, but on a two-year cycle, i.e., the tasks for SemEval-2016 were proposed in 2015. SemEval-2016 was co-located with the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT’2016) in San Diego, California. It included the following 14 shared tasks organized in five tracks: • Text Similarity and Question Answering Track – Task 1: Semantic Textual Similarity: A Unified Framework for Semantic Processing and Evaluation – Task 2: Interpretable Semantic Textual Similarity – Task 3: Community Question Answering • Sentiment Analysis Track – Task 4: Sentiment Analysis in Twitter – Task 5: Aspect-Based Sentiment Analysis – Task 6: Detecting Stance in Tweets – Task 7: Determining Sentiment Intensity of English and Arabic Phrases • Semantic Parsing Track – Task 8: Meaning Representation Parsing – Task 9: Chinese Semantic Dependency Parsing • Semantic Analysis Track – Task 10: Detecting Minimal Semantic Units and their Meanings – Task 11: Complex Word Identification – Task 12: Clinical TempEval iii • Semantic Taxonomy Track – Task 13: TExEval-2 – Taxonomy Extraction – Task 14: Semantic Taxonomy Enrichment This volume contains both Task Description papers that describe each of the above tasks and System Description papers that describe the systems that participated in the above tasks. A total of 14 task description papers and 198 system description papers are included in this volume. We are grateful to all task organisers as well as the large number of participants whose enthusiastic participation has made SemEval once again a successful event. We are thankful to the task organisers who also served as area chairs, and to task organisers and participants who reviewed paper submissions. These proceedings have greatly benefited from their detailed and thoughtful feedback. We also thank the NAACL 2016 conference organizers for their support. Finally, we most gratefully acknowledge the support of our sponsor, the ACL Special Interest Group on the Lexicon (SIGLEX). The SemEval-2016 organizers, Steven Bethard, Daniel Cer, Marine Carpuat, David Jurgens, Preslav Nakov and Torsten Zesch
In this paper, we consider opinion word extraction, one of the key problems in sentiment analysis. Sentiment analysis (or opinion mining) is an important research area within computational linguistics. Opinion words, which form an opinion lexicon, describe the attitude of the author towards certain opinion targets, i.e., entities and their attributes on which opinions have been expressed. Hence, the availability of a representative opinion lexicon can facilitate the extraction of opinions from texts. For this reason, opinion word mining is one of the key issues in sentiment analysis. We designed and implemented several methods for extracting opinion words. We evaluated these approaches by testing how well the resulting opinion lexicons help improve the accuracy of methods for determining the polarity of the reviews if the extracted opinion words are used as features. We used several machine learning methods: SVM, Logistic Regression, Naive Bayes, and KNN. By using the extracted opinion words as features we were able to improve over the baselines in some cases. Our experiments showed that, although opinion words are useful for polarity detection, they are not su fficient on their own and should be used only in combination with other features.
This article describes linguistic peculiarities of a column - one of the most popular and scantily explored genres of contemporary journalism. This genre, initially intended for commenting the political events, is undergoing transformation under the influence of non-professional authors, still keeping its basic features.
The paper examines the structure, governance, and balance sheets of state-controlled banks in Russia, which accounted for over 55 percent of the total assets in the country's banking system in early 2012. The author offers a credible estimate of the size of the country's state banking sector by including banks that are indirectly owned by public organizations. Contrary to some predictions based on the theoretical literature on economic transition, he explains the relatively high profitability and efficiency of Russian state-controlled banks by pointing to their competitive position in such functions as acquisition and disposal of assets on behalf of the government. Also suggested in the paper is a different way of looking at market concentration in Russia (by consolidating the market shares of core state-controlled banks), which produces a picture of a more concentrated market than officially reported. Lastly, one of the author's interesting conclusions is that China provides a better benchmark than the formerly centrally planned economies of Central and Eastern Europe by which to assess the viability of state ownership of banks in Russia and to evaluate the country's banking sector.
The paper examines the principles for the supervision of financial conglomerates proposed by BCBS in the consultative document published in December 2011. Moreover, the article proposes a number of suggestions worked out by the authors within the HSE research team.
портовый менеджмент, показатели деятельности, анализ эффективности, система учета, распределение издержек, методы анализа деятельности портовой системы
At present many industries reveal tendency for setting up of vertically integrated companies (VIC) the structure of which unites all technological processes. This tendency proved its efficiency in oil industry where coordination of all successive stages of technological process, namely, oil prospecting and production -oil transportation - oil processing - oil chemistry - oil products and oil chemicals marketing, is necessary. The article considers specific features of introduction of "personnel management" module at enterprises of oil and gas industry.
vertically integrated companies; personnel management