Data analysis through social media according to the classified crime

Topaloğlu, Nurettin

doi:10.3906/elk-1712-17

Cited by 17 publications

(12 citation statements)

References 37 publications

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“…( 2015 ). Discovering and disseminating events from diverse online social networks and with a variety of modes (e.g., text, image) have been the focus in many research studies, such as crypto-currencies Savaş ( 2021 ), crime intelligence SAVAŞ and TOPALOĞLU ( 2019 ), politics Adedoyin-Olowe et al. ( 2016 ), traffic analysis Alkouz and Al Aghbari ( 2020 ), and fashion analysis Wazarkar and Keshavamurthy ( 2020 ).…”

Section: Related Workmentioning

confidence: 99%

“…The dynamic updates of such events by the live communities in social media lay the ground for developing plenty of intelligent location-based services (LBSs). These LBSs can support a variety of domain applications, such as trip planning, emergency management, transportation, navigation, city exploration, education, and crime intelligence (Savaş and Topaloğlu 2017 ; SAVAŞ and TOPALOĞLU 2019 ).…”

Section: Introductionmentioning

confidence: 99%

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E-ware: a big data system for the incremental discovery of spatio-temporal events from microblogs

Afyouni

Khan

Alghbari

2022

J Ambient Intell Human Comput

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Event detection from social media aims at extracting specific or generic unusual happenings, such as, family reunions, earthquakes, and disease outbreaks, among others. This paper introduces a new perspective for the incremental extraction and clustering of social events from big social data streams. We present ‘E-ware’ , a scalable and efficient big data platform that integrates data stream and geospatial processing tools for the incremental extraction and dissemination of spatio-temporal events. We introduce a pure incremental approach for event discovery, by developing unsupervised machine learning and NLP algorithms and by computing events’ lifetime and spatial spanning. Our incremental clustering technique employs temporal sliding windows, in order to update the discovered topic clusters with the upcoming social streams (i.e., tweets). The system integrates an efficient spatio-temporal index for fast retrieval and updates of evolving event clusters. We conduct experiments over Twitter datasets to measure the effectiveness and efficiency of our system. The results demonstrate that E-ware has a major advantage for real-time incremental detection and tracking of events, both spatially and temporally. This leads to the development of unparalleled smart city applications, such as event-enriched trip planning, epidemic disease evolution, and proactive emergency management services.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

E-ware: a big data system for the incremental discovery of spatio-temporal events from microblogs

Afyouni

Khan

Alghbari

2022

J Ambient Intell Human Comput

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“…Cyber environments have now become real-life itself (Savaş and Topaloğlu 2019 ), and people spend most of the day in digital environments. For this reason, real-life threats can also be seen in digital environments.…”

Section: Conceptual Frameworkmentioning

confidence: 99%

Cyber governance studies in ensuring cybersecurity: an overview of cybersecurity governance

Karataş¹

2022

Int. Cybersecur. Law Rev.

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With the exponential increase of digital data in cyber environments, security measures have gained more importance. Cybersecurity threats are revealed by national and international units, and the number of these threats is increasing daily. The elimination of cybersecurity risks is possible with an effective cybersecurity strategy. Since the concept of management is not sufficient, the implementation of this strategy is possible with cyber governance, which includes all stakeholders in the management processes. This study emphasizes the importance and necessity of cyber governance in ensuring cybersecurity. The research and results for cybersecurity governance have been examined. A descriptive research model was used to this end. In terms of research philosophy, a basic research model and a documentary research model have been created with regard to the application method. The universe of the research consists of studies obtained from Web of Science, EBSCO, Scopus, Google Scholar, and TR Index. Studies from the last 5 years have been downloaded with the determined keywords. The result showed that although there are studies that produce local solutions for cybersecurity governance in different countries, a general governance framework has not been established as yet. On the contrary, there is a latent struggle to retain the management of this area, not its governance.

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“…After these operations, text normalization is performed. To do this, natural language processing tools such as NLTK [33] and Zemberek [34] are used to convert capital letters, convert numbers to text, remove punctuation and markups, remove spaces, open abbreviations and remove unnecessary words [35]. When there are a lot of texts to process, sometimes it is necessary to decrease the amount of the texts.…”

Section: A Natural Language Processing and Latent Semantic Analysismentioning

confidence: 99%

Türkçe Sözde Algoritma Kodu için LSTM Tabanlı Kaynak Kod Üretimi

İnce

2021

Düzce Üniversitesi Bilim Ve Teknoloji Dergisi

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Algorithmic thinking and programming abilities of students is controversial and popular issue in technological education programs in schools and universities. Students that have not best mathematical and analytical background may have difficulties in learning computer programing. Moreover, learning programming is highly difficult for a single individual to establish connection between discrete pseudo code of algorithm and source code. Another problem is required time to write a piece of program code. In order to solve this problem, there are some tools that tutor students to get analyze and realize relation between pseudo code and source code. In this study, we propose a deep learning method that is Long Short Term-Memory (LSTM) based source code generator from Turkish pseudo codes. For this purpose, we used Introduction to programming course exams in vocational high school as dataset to train LSTM. When users query a Turkish pseudo code of algorithm, C# source code is generated. In order to measure success of proposed system, generated source code and instructor's source code is analyzed with text similarity methods. Results show that proposed system is useful for students to learn fundamental programming skills.

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Data analysis through social media according to the classified crime

Cited by 17 publications

References 37 publications

E-ware: a big data system for the incremental discovery of spatio-temporal events from microblogs

E-ware: a big data system for the incremental discovery of spatio-temporal events from microblogs

Cyber governance studies in ensuring cybersecurity: an overview of cybersecurity governance

Türkçe Sözde Algoritma Kodu için LSTM Tabanlı Kaynak Kod Üretimi

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