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Sentiment based classification of the web texts
Jože Bučar, 2017

Abstract: It has always been a challenging task to predict events in the near or distant future. People are interested in forecasting weather, earthquakes, floods, predicting economic, political and social changes, as well as the development of technology, sales products and sports outcomes. On the web, an enormous quantity of data is generated daily. We are practically deluged by all kinds of data - scientific, medical, financial, historical, health care, demographic, business, and other. Usually, there are not enough human resources to examine this data. However, from this chaotic cluster of data we strive to obtain valuable information, which may significantly impact strategic decisions of both business and individuals in the future. Predicting future trends and events has become easier and more efficient especially with the collaboration among scientists from various fields. Sentiment analysis of web texts is an interesting and relevant research topic in this field. The aim of research described in this dissertation was to create specific language resources for sentiment analysis in Slovene, evaluate performance of sentiment based classification techniques and monitor the dynamics of sentiment, especially for the purpose of improving and contributing to computational analysis of texts in Slovene. Here, we introduce the construction of Slovene web-crawled news corpora and a lexicon for sentiment analysis in Slovene. Besides their availability, we describe the methodology and the tools that were required for their construction. The corpora contain more than 250,000 documents with political, business, economic and financial content from five Slovenian media resources on the web that were published between 1st of September 2007 and 31st of January 2016. They include sentiment annotation on three levels of granularity: sentence, paragraph and document level. More than 10,000 of them were manually annotated as positive, negative or neutral. A Slovene sentiment lexicon, which is based on the annotated documents, contains more than 25,000 words with sentiment ratings, and is the first of this kind for Slovene. In detail, we describe the construction of these language resources, the manual annotation process and its characteristics. All developed resources are publicly available under Creative Commons copyright license. We used the annotated documents to assess the sentiment classification approaches. Experimental performance evaluation of sentiment based classification techniques gives encouraging results. When classifying documents, in terms of time consumption and performance, the Multinational Naive Bayes and the Support Vector Machines approaches outperform the other classifiers. Also, consideration of smaller text segments, such as sentences, improves the performance. Models achieve F1-score value of 97,85 % within the two-class (positive and negative) and 77,76 % within the three-class (positive, negative and neutral) document-level sentiment based classification. The sentiment analysis methodology was successfully used in the real-world applications for estimating the proportions of positive, negative and neutral news in the selected web media, and for monitoring the dynamics of sentiment. When estimating the proportions of positive, negative and neutral news, approximately half of the retrieved news is neutral. In general, the proportion of negative news is twice as high as the proportion of positive news. The study of sentiment dynamics shows that sentiment is on average more explicit at the beginning of documents and loses sharpness towards the end.
Found in: ključnih besedah
Keywords: news corpus, sentiment analysis, lexicon, corpus linguistics, machine learning, document classification, monitoring sentiment dynamics
Published: 22.08.2018; Views: 2488; Downloads: 166
.pdf Fulltext (4,05 MB)

Social networks as factors for innovations
Victor Cepoi, 2018

Abstract: In the new local-global interconnection, nation states are losing their influence and legitimacy, while economic and cultural transformations are reconfiguring spatial formations. Going in line with the global trends, regions grasp more importance in shaping the political, economic and social environments. As a result, the regional level has an important role in creating a proper socio-economic framework for innovation development, which is considered one the engines of development. Relying on the theory of Social fields, the research considers three social forces (networks, institutions, and cognitive frames) as an alternative explanation for innovation processes, by encompassing the aspects of different social fields on the regional level. Consequently, within this dissertation we approach regional innovation systems as an analytical unit for exploring innovation performance of a regional environment. As case studies, we selected seven regions with different levels of innovation performance. The analysis of the semi-structured interviews and the Qualitative Comparative Analysis emphasized the social forces are a special component for explaining innovation processes in the selected case studies. Nonetheless, the results offer insights for regional mechanisms within the innovation performance with the focus on an approach toward innovation that is beyond simple economics.
Found in: ključnih besedah
Keywords: Regional Systems of Innovations, Networks, Social Field, Social Forces, Qualitative Comparative analysis
Published: 17.02.2020; Views: 1449; Downloads: 60
.pdf Fulltext (3,40 MB)

Public policy instrument evaluation in service of enabling grand strategy discourse
Alenka Pandiloska Jurak, 2019

Abstract: The purpose of the article is to illustrate the problem of public policy evaluation in regards to the availability of the information. By that, we want to warn about the issue of a disabled discourse of relevant social groups and institutions in the European Union. For this article, we evaluate public policy instrument H2020. The evaluation covers the availability of the data, that should enable interim and ex-post evaluation. The article offers a soulution to the emerging issue. Through the prism of Cultural political economy, the evaluation results also indicate the issue of Europe 2020 instruments retention. Consistency and transparency are not needed only throughout the different policies and strategy goals but also throughout their retention to assure the set goals.
Found in: ključnih besedah
Keywords: Cultural Political Economy, Europe 2020, evaluation, discourse, horizon, indicators, policy analysis
Published: 06.07.2020; Views: 1042; Downloads: 42
.pdf Fulltext (308,19 KB)

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