Pub Date : 2022-11-29DOI: 10.1109/snams58071.2022.10062553
E. Kanjo
Smart portable and wearable devices have become more and more popular in our lives due to their ability to "Wear and Use On-the-Go". However, in order to collect data and perform momentarily assessment of users' data, they require to be light weight, compact size with multiple sensors and higher processing capabilities. Edge computing provides an opportunity for wearable devices to access more resources without violating the constraints on weight, size, and sensing capabilities. Furthermore, edge computing (including TinyML) provides many required on-device processing capabilities which can then help in protecting users' private data as raw personal data (such as images and videos) don't need to be shared remotely. In this talk, I will look at the potential of edge computing to empower wearable and handheld devices while protecting users' privacy and I will showcase several examples of our recent work at the Smart Sensing lab including fidgeting cubes for mental health, edge and portable devices for Crime prevention and edge gadgets for location-based gaming and wellbeing. I will also provide a glimpse into exciting future directions that promise to have a profound impact on the Edge-Computing in the hands of users.
{"title":"Edge Computing in the Hands of Users","authors":"E. Kanjo","doi":"10.1109/snams58071.2022.10062553","DOIUrl":"https://doi.org/10.1109/snams58071.2022.10062553","url":null,"abstract":"Smart portable and wearable devices have become more and more popular in our lives due to their ability to \"Wear and Use On-the-Go\". However, in order to collect data and perform momentarily assessment of users' data, they require to be light weight, compact size with multiple sensors and higher processing capabilities. Edge computing provides an opportunity for wearable devices to access more resources without violating the constraints on weight, size, and sensing capabilities. Furthermore, edge computing (including TinyML) provides many required on-device processing capabilities which can then help in protecting users' private data as raw personal data (such as images and videos) don't need to be shared remotely. In this talk, I will look at the potential of edge computing to empower wearable and handheld devices while protecting users' privacy and I will showcase several examples of our recent work at the Smart Sensing lab including fidgeting cubes for mental health, edge and portable devices for Crime prevention and edge gadgets for location-based gaming and wellbeing. I will also provide a glimpse into exciting future directions that promise to have a profound impact on the Edge-Computing in the hands of users.","PeriodicalId":371668,"journal":{"name":"2022 Ninth International Conference on Social Networks Analysis, Management and Security (SNAMS)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116881087","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-29DOI: 10.1109/SNAMS58071.2022.10062823
A. Alshawabkeh, Faten F. Kharbat, Jamil Razmak
In the highly developed technological-focused periphery of modern industries, the need for channelizing knowledge among the members has gained increased importance. In this regard, a leading industrial sector, i.e., the hotel industry in the UK has been selected as the domain of this research to understand the prevailing impact of knowledge management (KM). To reach that, customer feedback on social media (Twitter and Facebook) through descriptive content analysis has been utilized to guide the systematic literature review analysis. The activities and reactions of customers on social media pages related to hospitality facilities were examined automatically using a text-mining algorithm through a script written in Python 3.8.5. the study pursues to understand the main patterns and practices of KM that can be found in the hotel industry from the literature review. Findings from the content analysis and systematic review of the literature revealed that KM would help the hotel industry in the UK to overcome many of the challenges they faced. It also would increase its capabilities and competencies, thereby offering greater competitive advantages.
{"title":"Knowledge Management Role in Enhancing Customer Relationship Management in Hotels Industry in the UK","authors":"A. Alshawabkeh, Faten F. Kharbat, Jamil Razmak","doi":"10.1109/SNAMS58071.2022.10062823","DOIUrl":"https://doi.org/10.1109/SNAMS58071.2022.10062823","url":null,"abstract":"In the highly developed technological-focused periphery of modern industries, the need for channelizing knowledge among the members has gained increased importance. In this regard, a leading industrial sector, i.e., the hotel industry in the UK has been selected as the domain of this research to understand the prevailing impact of knowledge management (KM). To reach that, customer feedback on social media (Twitter and Facebook) through descriptive content analysis has been utilized to guide the systematic literature review analysis. The activities and reactions of customers on social media pages related to hospitality facilities were examined automatically using a text-mining algorithm through a script written in Python 3.8.5. the study pursues to understand the main patterns and practices of KM that can be found in the hotel industry from the literature review. Findings from the content analysis and systematic review of the literature revealed that KM would help the hotel industry in the UK to overcome many of the challenges they faced. It also would increase its capabilities and competencies, thereby offering greater competitive advantages.","PeriodicalId":371668,"journal":{"name":"2022 Ninth International Conference on Social Networks Analysis, Management and Security (SNAMS)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116081760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-29DOI: 10.1109/SNAMS58071.2022.10062567
Diego Jacobs, A. Bobic, C. Gütl
To better understand publication data in the context of a single journal and potentially provide alternative measurements of scientific authors' performance and projected paper quality as a first step, this work analyzes journal data through social media analysis and natural language processing techniques. This paper describes the process of enriching and analyzing bibliometric data by creating a co-author network and calculating multiple node properties, which are compared to traditional bibliometric measurements. Furthermore, communities are extracted, and the averaged bibliometric properties of authors in those communities are compared to various community properties. Finally, the abstract and title length and readability were calculated and compared to the citation counts of respective papers. The comparison of the aforementioned values did not indicate a strong correlation among any of the values. However, some of the properties were slightly correlated. The analysis reveals that a single journal co-authorship network is not enough to extract meaningful alternative measurements for academic performance of authors or papers. However, it also indicates that network properties and readability measures could be potentially successfully leveraged to extract alternative performance indicators with a larger dataset.
{"title":"Comparison of Network and Readability Properties With Traditional Bibliometric Properties in the Journal of Universal Computer Science","authors":"Diego Jacobs, A. Bobic, C. Gütl","doi":"10.1109/SNAMS58071.2022.10062567","DOIUrl":"https://doi.org/10.1109/SNAMS58071.2022.10062567","url":null,"abstract":"To better understand publication data in the context of a single journal and potentially provide alternative measurements of scientific authors' performance and projected paper quality as a first step, this work analyzes journal data through social media analysis and natural language processing techniques. This paper describes the process of enriching and analyzing bibliometric data by creating a co-author network and calculating multiple node properties, which are compared to traditional bibliometric measurements. Furthermore, communities are extracted, and the averaged bibliometric properties of authors in those communities are compared to various community properties. Finally, the abstract and title length and readability were calculated and compared to the citation counts of respective papers. The comparison of the aforementioned values did not indicate a strong correlation among any of the values. However, some of the properties were slightly correlated. The analysis reveals that a single journal co-authorship network is not enough to extract meaningful alternative measurements for academic performance of authors or papers. However, it also indicates that network properties and readability measures could be potentially successfully leveraged to extract alternative performance indicators with a larger dataset.","PeriodicalId":371668,"journal":{"name":"2022 Ninth International Conference on Social Networks Analysis, Management and Security (SNAMS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129043232","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-29DOI: 10.1109/SNAMS58071.2022.10062668
André Schmale, Volker Mittendorf
This article examines negative campaigning on Twitter against individual actors of the Green Party or against the party itself around the 2021 federal election in Germany. Based on hashtags and accounts, the various discourse elements from the social media are reconstructed and analyzed as a conceptual and thematic network. In doing so, the data will be examined using quantitative text analysis, sentiment analysis, dictionary-based comparison of populist communication style, and structural topic model. In addition, the framework of political discourse analysis is used to better interpret negative campaigning in context.
{"title":"Detecting Negative Campaigning on Twitter Against The Greens","authors":"André Schmale, Volker Mittendorf","doi":"10.1109/SNAMS58071.2022.10062668","DOIUrl":"https://doi.org/10.1109/SNAMS58071.2022.10062668","url":null,"abstract":"This article examines negative campaigning on Twitter against individual actors of the Green Party or against the party itself around the 2021 federal election in Germany. Based on hashtags and accounts, the various discourse elements from the social media are reconstructed and analyzed as a conceptual and thematic network. In doing so, the data will be examined using quantitative text analysis, sentiment analysis, dictionary-based comparison of populist communication style, and structural topic model. In addition, the framework of political discourse analysis is used to better interpret negative campaigning in context.","PeriodicalId":371668,"journal":{"name":"2022 Ninth International Conference on Social Networks Analysis, Management and Security (SNAMS)","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130158434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-29DOI: 10.1109/SNAMS58071.2022.10062796
Carl Terve, Mattias Erlingsson, Alireza Mohammadinodooshan, Niklas Carlsson
The discussions on social-media forums can impact the sentiment of a company, and consequently also its stock price. As we show here, some of the most shorted companies have provided some of the clearest examples of this relationship. In light of these observations, this paper presents a longitudinal study of the cross-forum dynamics of ten highly shorted stocks that saw significant discussions on the popular forums Reddit, Twitter, and Seeking Alpha. Using the posts from these forums, their sentiments, and the daily snapshots of the stock price of each company, we use a combination of qualitative case studies and quantitative hypothesis testing to derive new insights. Through a combination of time-series analysis, clustering, and domain-optimized sentiment analysis, we study the relationship between the times that discussions peak on the different forums, the changes in sentiment, and the stock price movements. We find that all three forums are likely to experience peaks in their activity close to each other, that Reddit is most likely to peak first, and that the sentiment of Twitter discussions were more sensitive to the current derivative of the stock price than the sentiment observed on the other forums.
{"title":"Social Media Dynamics of Shorted Companies","authors":"Carl Terve, Mattias Erlingsson, Alireza Mohammadinodooshan, Niklas Carlsson","doi":"10.1109/SNAMS58071.2022.10062796","DOIUrl":"https://doi.org/10.1109/SNAMS58071.2022.10062796","url":null,"abstract":"The discussions on social-media forums can impact the sentiment of a company, and consequently also its stock price. As we show here, some of the most shorted companies have provided some of the clearest examples of this relationship. In light of these observations, this paper presents a longitudinal study of the cross-forum dynamics of ten highly shorted stocks that saw significant discussions on the popular forums Reddit, Twitter, and Seeking Alpha. Using the posts from these forums, their sentiments, and the daily snapshots of the stock price of each company, we use a combination of qualitative case studies and quantitative hypothesis testing to derive new insights. Through a combination of time-series analysis, clustering, and domain-optimized sentiment analysis, we study the relationship between the times that discussions peak on the different forums, the changes in sentiment, and the stock price movements. We find that all three forums are likely to experience peaks in their activity close to each other, that Reddit is most likely to peak first, and that the sentiment of Twitter discussions were more sensitive to the current derivative of the stock price than the sentiment observed on the other forums.","PeriodicalId":371668,"journal":{"name":"2022 Ninth International Conference on Social Networks Analysis, Management and Security (SNAMS)","volume":"319 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122434246","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-29DOI: 10.1109/SNAMS58071.2022.10062613
Mariam Al Akasheh, Nehal Eleyan, Gürdal Ertek
Online food delivery (OFD) has become a popular and profitable e-business category due to the rising demand for online food delivery. People are increasingly ordering food online, especially in urban areas and on college campuses. Using data from online food delivery services, one can analyze and predict the values of key performance indicators (KPIs). In the study presented in this paper, we developed a systematic methodology to analyze and predict such KPIs using various classification and regression algorithms. We found that, for the case study we analyzed, Random Forest (RF) consistently ranked as the best algorithm for regression and classification in predicting most of the KPIs. The methodology we introduce and illustrate in the paper can be adapted and extended to similar problems to reveal potential operational issues and identify the possible root causes of such problems.
{"title":"A Predictive Data Analytics Methodology for Online Food Delivery","authors":"Mariam Al Akasheh, Nehal Eleyan, Gürdal Ertek","doi":"10.1109/SNAMS58071.2022.10062613","DOIUrl":"https://doi.org/10.1109/SNAMS58071.2022.10062613","url":null,"abstract":"Online food delivery (OFD) has become a popular and profitable e-business category due to the rising demand for online food delivery. People are increasingly ordering food online, especially in urban areas and on college campuses. Using data from online food delivery services, one can analyze and predict the values of key performance indicators (KPIs). In the study presented in this paper, we developed a systematic methodology to analyze and predict such KPIs using various classification and regression algorithms. We found that, for the case study we analyzed, Random Forest (RF) consistently ranked as the best algorithm for regression and classification in predicting most of the KPIs. The methodology we introduce and illustrate in the paper can be adapted and extended to similar problems to reveal potential operational issues and identify the possible root causes of such problems.","PeriodicalId":371668,"journal":{"name":"2022 Ninth International Conference on Social Networks Analysis, Management and Security (SNAMS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131828342","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-29DOI: 10.1109/SNAMS58071.2022.10062688
Malak Abdullah, Alia Madain, Y. Jararweh
Recent progress in large language models has pushed the boundaries of natural language processing, setting new standards for performance. It is remarkable how artificial intelligence can mimic human behavior and writing style in such a convincing way. As a result, it is hard to tell if a human or a machine wrote something. Deep learning and natural language processing have recently advanced large language models. These newer models can learn from large amounts of data to better capture the nuances of language, making them more accurate and robust than ever before. Additionally, these models can now be applied to tasks such as summarizing text, translating between languages, and even generating original content. ChatGPT is a natural language processing (NLP) model developed in 2022 by OpenAI for open-ended conversations. It is based on GPT-3.5, the third-generation language processing model from OpenAI. ChatGPT can power conversational AI applications like virtual assistants and chatbots. In this paper, we describe the current version of ChatGPT and discuss the model's potential and possible social impact. Disclaimer: This paper was not written by ChatGPT: it was written by the listed authors.
{"title":"ChatGPT: Fundamentals, Applications and Social Impacts","authors":"Malak Abdullah, Alia Madain, Y. Jararweh","doi":"10.1109/SNAMS58071.2022.10062688","DOIUrl":"https://doi.org/10.1109/SNAMS58071.2022.10062688","url":null,"abstract":"Recent progress in large language models has pushed the boundaries of natural language processing, setting new standards for performance. It is remarkable how artificial intelligence can mimic human behavior and writing style in such a convincing way. As a result, it is hard to tell if a human or a machine wrote something. Deep learning and natural language processing have recently advanced large language models. These newer models can learn from large amounts of data to better capture the nuances of language, making them more accurate and robust than ever before. Additionally, these models can now be applied to tasks such as summarizing text, translating between languages, and even generating original content. ChatGPT is a natural language processing (NLP) model developed in 2022 by OpenAI for open-ended conversations. It is based on GPT-3.5, the third-generation language processing model from OpenAI. ChatGPT can power conversational AI applications like virtual assistants and chatbots. In this paper, we describe the current version of ChatGPT and discuss the model's potential and possible social impact. Disclaimer: This paper was not written by ChatGPT: it was written by the listed authors.","PeriodicalId":371668,"journal":{"name":"2022 Ninth International Conference on Social Networks Analysis, Management and Security (SNAMS)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134362087","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-29DOI: 10.1109/iotsms58070.2022.10062002
Paolo Rosso
The rise of social media has offered a fast and easy way for the propagation of fake news and conspiracy theories. Despite the research attention that has received, fake news detection remains an open problem and users keep sharing texts that contain false statements. In this keynote I will describe how to go beyond textual information to detect fake news, taking into account also affective and visual information because providing important insights on how fake news spreaders aim at triggering certain emotions in the readers. I will also describe how psycholinguistic patterns and users' personality traits may play an important role in discriminating fake news spreaders from fact checkers. Finally, I will comment on some studies on the propagation of conspiracy theories. The ongoing work done on detection of disinformation, from fake news to conspiracy theories, is in the framework of IBERIFIER, the Iberian media research & fact-checking hub on disinformation funded by the European Digital Media Observatory (2020-EU-IA-0252), and the XAI-DisInfodemics project on eXplainable AI for disinformation and conspiracy detection during infodemics funded by the Spanish Ministry of Science and Innovation (PLEC2021-007681). In the final part of the keynote I will address also the other side of harmful information in social media, hate speech, making emphasis on the case of misogynous memes.
{"title":"On the Detection of Fake News, Conspiracy Theories, and Hate Speech Spreaders","authors":"Paolo Rosso","doi":"10.1109/iotsms58070.2022.10062002","DOIUrl":"https://doi.org/10.1109/iotsms58070.2022.10062002","url":null,"abstract":"The rise of social media has offered a fast and easy way for the propagation of fake news and conspiracy theories. Despite the research attention that has received, fake news detection remains an open problem and users keep sharing texts that contain false statements. In this keynote I will describe how to go beyond textual information to detect fake news, taking into account also affective and visual information because providing important insights on how fake news spreaders aim at triggering certain emotions in the readers. I will also describe how psycholinguistic patterns and users' personality traits may play an important role in discriminating fake news spreaders from fact checkers. Finally, I will comment on some studies on the propagation of conspiracy theories. The ongoing work done on detection of disinformation, from fake news to conspiracy theories, is in the framework of IBERIFIER, the Iberian media research & fact-checking hub on disinformation funded by the European Digital Media Observatory (2020-EU-IA-0252), and the XAI-DisInfodemics project on eXplainable AI for disinformation and conspiracy detection during infodemics funded by the Spanish Ministry of Science and Innovation (PLEC2021-007681). In the final part of the keynote I will address also the other side of harmful information in social media, hate speech, making emphasis on the case of misogynous memes.","PeriodicalId":371668,"journal":{"name":"2022 Ninth International Conference on Social Networks Analysis, Management and Security (SNAMS)","volume":"272 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134502884","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-29DOI: 10.1109/snams58071.2022.10062752
M. Kandeel, H. Salameh, G. Elrefae, Amer Qasim
Drone technology has undergone dramatic changes in recent years due to advancements in information and communication technologies, the internet of things, and robotic process automation. As a result, various applications of this technology have emerged and affected many aspects of everyday activities. Considering the diverse areas in which drones are used, it is deemed necessary to develop legal controls over these uses in order to achieve national, regional, or international purposes. For legal regulation of drones to take place, there should be bodies or institutions in charge of the implementation of the legislation regulating drone uses, operations, and related activities, in accordance with international treaties and agreements. This paper argues that the diversity and development of the activities in which the drone is used require the establishment of legal controls to regulate its authorization including that of activities, types, designs, manufacturing, importing, selling, owning, registration, as well as protecting third party's right to data privacy and confidentiality. Drone legislation is needed to regulate issues related to compensation for damages arising from activities associated with drones, and to setting conditions, requirements, and procedures for the use of drone radio frequencies, systems, and remote control stations. Rules also have a significant role in monitoring the establishment of the infrastructure implementing the operation of these aircraft, their airports, the mechanism for supplying fuel and energy, and the issuance of an operational safety certificate. Finally, the regulation is required for maintaining control on safety issues such as airspace planning and routing, altitude and horizontal operation of operations, entry, and exit from airspace, designation of prohibited, restricted, or dangerous areas, and airspace use obligations.
{"title":"Regulations for UAV Operation in Social Applications and Services: A General Perspective","authors":"M. Kandeel, H. Salameh, G. Elrefae, Amer Qasim","doi":"10.1109/snams58071.2022.10062752","DOIUrl":"https://doi.org/10.1109/snams58071.2022.10062752","url":null,"abstract":"Drone technology has undergone dramatic changes in recent years due to advancements in information and communication technologies, the internet of things, and robotic process automation. As a result, various applications of this technology have emerged and affected many aspects of everyday activities. Considering the diverse areas in which drones are used, it is deemed necessary to develop legal controls over these uses in order to achieve national, regional, or international purposes. For legal regulation of drones to take place, there should be bodies or institutions in charge of the implementation of the legislation regulating drone uses, operations, and related activities, in accordance with international treaties and agreements. This paper argues that the diversity and development of the activities in which the drone is used require the establishment of legal controls to regulate its authorization including that of activities, types, designs, manufacturing, importing, selling, owning, registration, as well as protecting third party's right to data privacy and confidentiality. Drone legislation is needed to regulate issues related to compensation for damages arising from activities associated with drones, and to setting conditions, requirements, and procedures for the use of drone radio frequencies, systems, and remote control stations. Rules also have a significant role in monitoring the establishment of the infrastructure implementing the operation of these aircraft, their airports, the mechanism for supplying fuel and energy, and the issuance of an operational safety certificate. Finally, the regulation is required for maintaining control on safety issues such as airspace planning and routing, altitude and horizontal operation of operations, entry, and exit from airspace, designation of prohibited, restricted, or dangerous areas, and airspace use obligations.","PeriodicalId":371668,"journal":{"name":"2022 Ninth International Conference on Social Networks Analysis, Management and Security (SNAMS)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127910818","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-29DOI: 10.1109/SNAMS58071.2022.10062756
Khadija Alhumaid, Kevin Ayoubi, M. Habes, M. Elareshi, S. Salloum
The key objective of our study involves devising a conceptual model for estimation of social media acceptance by students for effectively accomplishing their educational and academic goals. Factors e.g., perceived social capital, social influence, and perceived mobility that associated with student acceptance of social media were investigated, and integrated into the TAM model using the PLS-SEM. Data were collected through online survey (461 students) at UAE universities. The findings revealed that mentioned factors positively affected students' intention to use social media during their learning process. Respondents' behavioral intention were also linked to both the core and external constructs of the TAM. Important practical insights on technology acceptance in education were provided.
{"title":"Social Media Acceptance and e-Learning Post-Covid-19: New factors determine the extension of TAM","authors":"Khadija Alhumaid, Kevin Ayoubi, M. Habes, M. Elareshi, S. Salloum","doi":"10.1109/SNAMS58071.2022.10062756","DOIUrl":"https://doi.org/10.1109/SNAMS58071.2022.10062756","url":null,"abstract":"The key objective of our study involves devising a conceptual model for estimation of social media acceptance by students for effectively accomplishing their educational and academic goals. Factors e.g., perceived social capital, social influence, and perceived mobility that associated with student acceptance of social media were investigated, and integrated into the TAM model using the PLS-SEM. Data were collected through online survey (461 students) at UAE universities. The findings revealed that mentioned factors positively affected students' intention to use social media during their learning process. Respondents' behavioral intention were also linked to both the core and external constructs of the TAM. Important practical insights on technology acceptance in education were provided.","PeriodicalId":371668,"journal":{"name":"2022 Ninth International Conference on Social Networks Analysis, Management and Security (SNAMS)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116773263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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