Open-Source Monitoring, Search and Analytics Over Social Media

Schinas, Manos; Papadopoulos, Symeon; Apostolidis, Lazaros; Kompatsiaris, Ioannis; Mitkas, Pericles A.

doi:10.1007/978-3-319-70284-1_28

Cited by 7 publications

(6 citation statements)

References 5 publications

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“…The confusion matrix shows true and false predictions for every class. In the multiclass (20) The greater the value of an area, the better the classification model's performance is. Although the AUC-ROC metric is a very important metric for evaluating the performance of models, it is standardly used for binary classification problems.…”

Section: Multiclass Classification Metricsmentioning

confidence: 99%

On the development of an information system for monitoring user opinion and its role for the public

et al. 2022

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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.

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Section: Multiclass Classification Metricsmentioning

confidence: 99%

On the development of an information system for monitoring user opinion and its role for the public

et al. 2022

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“…Data was collected from Twitter using a web crawler that searches through particular hashtags. [9] demonstrates an open framework for monitoring, analyzing, and receiving media content. This framework allows you to collect, index, and retrieve data using the Representational state transfer application programming interface (REST API) from the following sources: Twitter, Facebook, YouTube, Google +, and Flickr.…”

Section: Related Workmentioning

confidence: 99%

On the Development of an Information System for Monitoring User Opinion and its Role for the Public

Karyukin¹,

Mutanov²,

Mamykova³

et al. 2021

Preprint

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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. In the experimental part, the system’s monitoring of the healthcare, political and social aspects of the most relevant topics connected with the vaccination against the coronavirus disease are thoroughly observed and analyzed. The analysis allowed discovering 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 mood and attitude 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 to vaccination, etc.) and assessment of the social mood.

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“…The tool builds upon and extends an open-source software framework (https://github.com/MKLab-ITI/mmdemo-dockerized) [45] for monitoring, analysis, and search over …”

Section: Social Media Monitoring Tools For Relevant User Discoverymentioning

confidence: 99%

“…The tool builds upon and extends an open-source software framework (https://github.com/ MKLab-ITI/mmdemo-dockerized) [45] for monitoring, analysis, and search over multiple social media platforms. The framework offers powerful tools for (a) tracking social media discussions around keywords and user accounts of interest; (b) obtaining real-time analytics over the tracked keywords/accounts; (c) identifying new accounts; and (d) analyzing the structure of communities.…”

Section: Social Media Monitoring Tools For Relevant User Discoverymentioning

confidence: 99%

hackAIR: Towards Raising Awareness about Air Quality in Europe by Developing a Collective Online Platform

Kosmidis

Syropoulou

Tekes

et al. 2018

IJGI

Self Cite

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Abstract:Although air pollution is one of the most significant environmental factors posing a threat to human health worldwide, air quality data are scarce or not easily accessible in most European countries. The current work aims to develop a centralized air quality data hub that enables citizens to contribute to air quality monitoring. In this work, data from official air quality monitoring stations are combined with air pollution estimates from sky-depicting photos and from low-cost sensing devices that citizens build on their own so that citizens receive improved information about the quality of the air they breathe. Additionally, a data fusion algorithm merges air quality information from various sources to provide information in areas where no air quality measurements exist.

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Open-Source Monitoring, Search and Analytics Over Social Media

Cited by 7 publications

References 5 publications

On the development of an information system for monitoring user opinion and its role for the public

On the development of an information system for monitoring user opinion and its role for the public

On the Development of an Information System for Monitoring User Opinion and its Role for the Public

hackAIR: Towards Raising Awareness about Air Quality in Europe by Developing a Collective Online Platform

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