7 results on '"analytics platforms"'
Search Results
2. On the development of an information system for monitoring user opinion and its role for the public
- Author
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Vladislav Karyukin, Galimkair Mutanov, Zhanl Mamykova, Gulnar Nassimova, Saule Torekul, Zhanerke Sundetova, and Matteo Negri
- Subjects
Social media ,Social networks ,Social mood ,Sentiment analysis ,Analytics platforms ,Sentiment dictionary ,Computer engineering. Computer hardware ,TK7885-7895 ,Information technology ,T58.5-58.64 ,Electronic computers. Computer science ,QA75.5-76.95 - Abstract
Abstract Social media services and analytics platforms are rapidly growing. A large number of various events happen mostly every day, and the role of social media monitoring tools is also increasing. Social networks are widely used for managing and promoting brands and different services. Thus, most popular social analytics platforms aim for business purposes while monitoring various social, economic, and political problems remains underrepresented and not covered by thorough research. Moreover, most of them focus on resource-rich languages such as the English language, whereas texts and comments in other low-resource languages, such as the Russian and Kazakh languages in social media, are not represented well enough. So, this work is devoted to developing and applying the information system called the OMSystem for analyzing users’ opinions on news portals, blogs, and social networks in Kazakhstan. The system uses sentiment dictionaries of the Russian and Kazakh languages and machine learning algorithms to determine the sentiment of social media texts. The whole structure and functionalities of the system are also presented. The experimental part is devoted to building machine learning models for sentiment analysis on the Russian and Kazakh datasets. Then the performance of the models is evaluated with accuracy, precision, recall, and F1-score metrics. The models with the highest scores are selected for implementation in the OMSystem. Then the OMSystem’s social analytics module is used to thoroughly analyze the healthcare, political and social aspects of the most relevant topics connected with the vaccination against the coronavirus disease. The analysis allowed us to discover the public social mood in the cities of Almaty and Nur-Sultan and other large regional cities of Kazakhstan. The system’s study included two extensive periods: 10-01-2021 to 30-05-2021 and 01-07-2021 to 12-08-2021. In the obtained results, people’s moods and attitudes to the Government’s policies and actions were studied by such social network indicators as the level of topic discussion activity in society, the level of interest in the topic in society, and the mood level of society. These indicators calculated by the OMSystem allowed careful identification of alarming factors of the public (negative attitude to the government regulations, vaccination policies, trust in vaccination, etc.) and assessment of the social mood.
- Published
- 2022
- Full Text
- View/download PDF
3. On the development of an information system for monitoring user opinion and its role for the public.
- Author
-
Karyukin, Vladislav, Mutanov, Galimkair, Mamykova, Zhanl, Nassimova, Gulnar, Torekul, Saule, Sundetova, Zhanerke, and Negri, Matteo
- Subjects
PUBLIC opinion ,INFORMATION storage & retrieval systems ,SENTIMENT analysis ,PROGRAMMING languages ,COVID-19 ,SOCIAL media ,BIG data ,MACHINE learning - Abstract
Social media services and analytics platforms are rapidly growing. A large number of various events happen mostly every day, and the role of social media monitoring tools is also increasing. Social networks are widely used for managing and promoting brands and different services. Thus, most popular social analytics platforms aim for business purposes while monitoring various social, economic, and political problems remains underrepresented and not covered by thorough research. Moreover, most of them focus on resource-rich languages such as the English language, whereas texts and comments in other low-resource languages, such as the Russian and Kazakh languages in social media, are not represented well enough. So, this work is devoted to developing and applying the information system called the OMSystem for analyzing users' opinions on news portals, blogs, and social networks in Kazakhstan. The system uses sentiment dictionaries of the Russian and Kazakh languages and machine learning algorithms to determine the sentiment of social media texts. The whole structure and functionalities of the system are also presented. The experimental part is devoted to building machine learning models for sentiment analysis on the Russian and Kazakh datasets. Then the performance of the models is evaluated with accuracy, precision, recall, and F1-score metrics. The models with the highest scores are selected for implementation in the OMSystem. Then the OMSystem's social analytics module is used to thoroughly analyze the healthcare, political and social aspects of the most relevant topics connected with the vaccination against the coronavirus disease. The analysis allowed us to discover the public social mood in the cities of Almaty and Nur-Sultan and other large regional cities of Kazakhstan. The system's study included two extensive periods: 10-01-2021 to 30-05-2021 and 01-07-2021 to 12-08-2021. In the obtained results, people's moods and attitudes to the Government's policies and actions were studied by such social network indicators as the level of topic discussion activity in society, the level of interest in the topic in society, and the mood level of society. These indicators calculated by the OMSystem allowed careful identification of alarming factors of the public (negative attitude to the government regulations, vaccination policies, trust in vaccination, etc.) and assessment of the social mood. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
4. IoT platforms for the Mining Industry: An Overview.
- Author
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GACKOWIEC, Paulina and PODOBIŃSKA-STANIEC, Marta
- Subjects
MINERAL industries ,INTERNET of things ,MINING methodology ,ARTIFICIAL intelligence ,MANUFACTURING processes ,VISUAL analytics ,INTERNETWORKING - Abstract
Copyright of Inzynieria Mineralna is the property of Polskie Towarzystwo Przerobki Kopalin and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
- Published
- 2019
- Full Text
- View/download PDF
5. Opportunities for the Use of Business Data Analysis Technologies
- Author
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Bāliņa Signe, Žuka Rita, and Krasts Juris
- Subjects
analytics platforms ,business analytics ,business intelligence ,data mining ,online analytical processing ,predictive modelling ,Business ,HF5001-6182 ,Economics as a science ,HB71-74 - Abstract
The paper analyses the business data analysis technologies, provides their classification and considers relevant terminology. The feasibility of business data analysis technologies handling big data sources is overviewed. The paper shows the results of examination of the online big data source analytics technologies, data mining and predictive modelling technologies and their trends.
- Published
- 2016
- Full Text
- View/download PDF
6. Opportunities for the Use of Business Data Analysis Technologies
- Author
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Signe Bāliņa, Rita Žuka, and Juris Krasts
- Subjects
0209 industrial biotechnology ,Engineering ,HF5001-6182 ,Big data ,online analytical processing ,02 engineering and technology ,Analytics platforms ,business intelligence ,Terminology ,Business data ,020901 industrial engineering & automation ,Business analytics ,0502 economics and business ,analytics platforms ,Business ,HB71-74 ,business.industry ,Management science ,Online analytical processing ,05 social sciences ,business analytics ,data mining ,predictive modelling ,Data science ,Economics as a science ,Analytics ,Business intelligence ,business ,050203 business & management ,Predictive modelling - Abstract
The paper analyses the business data analysis technologies, provides their classification and considers relevant terminology. The feasibility of business data analysis technologies handling big data sources is overviewed. The paper shows the results of examination of the online big data source analytics technologies, data mining and predictive modelling technologies and their trends.
- Published
- 2016
7. Two Wall Street Giants Are Going to Be Linking Their Customers’ Data.
- Author
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Baer, Justin
- Subjects
- *
INFORMATION sharing , *BUSINESS revenue , *BUSINESS planning , *INVESTMENTS - Published
- 2019
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