Social Networking Services (SNS) have gained immense popularity in developing countries like Indi... more Social Networking Services (SNS) have gained immense popularity in developing countries like India, where digital natives are actively communicating on these platforms. Understanding the interaction between technology systems and digital natives, and proposing guidelines and recommendations for the development of better systems is highly valuable. Prior research examining users’ motivations and actual usage of photo tagging systems is limited, and predominately focused on Flickr and adult users. In order to understand in detail why, how, and with whom users tag digital photos on Facebook, a qualitative essaybased exploratory study is organized with 67 digital natives in India. The study aims to build understanding of the various gratifications, motivations, experiences, and practices associated with Facebook photo tagging, focusing on technologically savvy Indian digital natives. Our results reveal that photo tagging practices by digital natives vary substantially, especially among ...
BACKGROUND Online debates surrounding face masks as a precautionary measure against COVID-19 pand... more BACKGROUND Online debates surrounding face masks as a precautionary measure against COVID-19 pandemic have been raging on social media platforms like Twitter. Users against or in favor of masks have be vocal in sharing their opinions about the masks wearing, practices, and consequences. Through a social network analysis (SNA), we unearth the important contributors to the debate on Twitter surrounding pro and anti-masks. OBJECTIVE The aim of this study is to develop an understanding of the content and influencers on Twitter related to anti-mask and pro-mask debates. METHODS In this study 18,000 tweets related to keywords that were either pro mask and anti-mask from 12th December 2020, to 18th December 2020, and 18,000 tweets from 9th of December to the 18th of December 2020. The two datasets were analysed using social network analysis in Gephi, meanwhile NodeXL was used to produce network metrics and identify the key users, websites, and content within the data. RESULTS Discussions f...
Each year, significant investment of time and resources is made to improve diversity within engin... more Each year, significant investment of time and resources is made to improve diversity within engineering across a range of federal and state agencies, private/not-for-profit organizations, and foundations. In spite of decades of investments, efforts have not yielded desired returns - participation by minorities continues to lag at a time when STEM workforce requirements are increasing. In recent years a new stream of data has emerged - online social networks, including Twitter, Facebook, and Instagram - that act as a key sensor of social behavior and attitudes of the public. Almost 87% of the American population now participates in some form of social media activity. Consequently, social networking sites have become powerful indicators of social action and social media data has shown significant promise for studying many issues including public health communication, political campaign, humanitarian crisis, and, activism. We argue that social media data can likewise be leveraged to be...
Social media provides a mechanism for people to engage with social causes across a range of issue... more Social media provides a mechanism for people to engage with social causes across a range of issues. It also provides a strategic tool to those looking to advance a cause to exchange, promote or publicize their ideas. In such instances, AI can be either an asset if used appropriately or a barrier. One of the key issues for a workforce diversity campaign is to understand in real-time who is participating - specifically, whether the participants are individuals or organizations, and in case of individuals, whether they are male or female. In this paper, we present a study to demonstrate a case for AI for social good that develops a model to infer in real-time the different user types participating in a cause-driven hashtag campaign on Twitter, ILookLikeAnEngineer (ILLAE). A generic framework is devised to classify a Twitter user into three classes: organization, male and female in a real-time manner. The framework is tested against two datasets (ILLAE and a general dataset) and outperf...
Social media provides a mechanism for people to engage with social causes across a range of issue... more Social media provides a mechanism for people to engage with social causes across a range of issues. It also provides a strategic tool to those looking to advance a cause to exchange, promote or publicize their ideas. In such instances, AI can be either an asset if used appropriately or a barrier. One of the key issues for a workforce diversity campaign is to understand in real-time who is participating - specifically, whether the participants are individuals or organizations, and in case of individuals, whether they are male or female. In this paper, we present a study to demonstrate a case for AI for social good that develops a model to infer in real-time the different user types participating in a cause-driven hashtag campaign on Twitter, ILookLikeAnEngineer (ILLAE). A generic framework is devised to classify a Twitter user into three classes: organization, male and female in a real-time manner. The framework is tested against two datasets (ILLAE and a general dataset) and outperf...
Social Networking Services (SNS) have gained immense popularity in developing countries like Indi... more Social Networking Services (SNS) have gained immense popularity in developing countries like India, where digital natives are actively communicating on these platforms. Understanding the interaction between technology systems and digital natives, and proposing guidelines and recommendations for the development of better systems is highly valuable. Prior research examining users’ motivations and actual usage of photo tagging systems is limited, and predominately focused on Flickr and adult users. In order to understand in detail why, how, and with whom users tag digital photos on Facebook, a qualitative essaybased exploratory study is organized with 67 digital natives in India. The study aims to build understanding of the various gratifications, motivations, experiences, and practices associated with Facebook photo tagging, focusing on technologically savvy Indian digital natives. Our results reveal that photo tagging practices by digital natives vary substantially, especially among ...
The novel settings provided by social media facilitate users to seek and share information on a w... more The novel settings provided by social media facilitate users to seek and share information on a wide array of subjects, including healthcare and wellness. Analyzing health-related opinions and discussions on these platforms complement traditional public health surveillance systems to support timely and effective interventions. This study aims to characterize the HIV-related conversations on Twitter by identifying the prevalent topics and the key events and actors involved in these discussions. Through Twitter API, we collected tweets containing the hashtag #HIV for a one-year period. After pre-processing the collected data, we conducted engagement analysis, temporal analysis, and topic modeling algorithm on the analytical sample (n = 122,807). Tweets by HIV/AIDS/LGBTQ activists and physicians received the highest level of engagement. An upsurge in tweet volume and engagement was observed during global and local events such as World Aids Day and HIV/AIDS awareness and testing days fo...
The International Arab Journal of Information Technology
With the advancement in wireless communication technology, the ease of accessibility and increasi... more With the advancement in wireless communication technology, the ease of accessibility and increasing coverage area is a major challenge for service providers. Network densification through Small cell Base Stations (SBS) integration in Heterogeneous Networks (HetNets) promises to improve network performance for cell edge users. Since providing wired backhaul for small cells is not cost effective or practical, the third-Generation Partnership Project (3GPP) has developed architecture for self-backhaul known as Integrated Access and Backhaul (IAB) for Fifth Generation (5G). This allows for Main Base Station (MBS) resources to be shared between SBS and MBS users. However, fair and efficient division of MBS resources remains a problem to be addressed. We develop a novel transmit antenna selection/partitioning technique for taking advantage of IAB 5G standard for Massive Multiple Input Multiple Output (MIMO) HetNets. Transmit antenna resources are divided among access for MBS users and for...
Introduction The availability of a variety of e-cigarettes flavors is one of the frequently cited... more Introduction The availability of a variety of e-cigarettes flavors is one of the frequently cited reasons for their adoption. An active stream of discussion about flavoring can be observed online. Analyzing these real-time conversations offers nuanced insights into key factors related to the adoption of flavors, subsequently supporting public health interventions. Methods Google’s BERT, a state-of-the-art deep learning method was employed to model the first sentiment corpus on JUUL flavors. BERT, which is pre-trained with the complete English Wikipedia was fine-tuned by integrating a classification model, with human labeled Tweets, as training data. A collection of 30 075 Tweets about JUUL flavors was classified into positive and negative sentiments. Finally, using topic models, we identify and grouped thematic areas into positive and negative Tweets. Results With an average of 89% cross-validation precision for classifying Tweets, the fine-tuned BERT model classified 24 114 Tweets ...
Deceptive jamming is a popular electronic countermeasure (ECM) technique that generates false tar... more Deceptive jamming is a popular electronic countermeasure (ECM) technique that generates false targets to confuse opponent surveillance radars. This work presents a novel approach for hiding the actual target while producing multiple false targets at the same time against frequency diverse array (FDA) radar. For this purpose, the modified FDA radar is assumed to be mounted on the actual aircraft. It intercepts the opponent’s radar signals and transmits back to place nulls in the radiation pattern at the desired range and direction to exploit FDA radar’s range-dependent pattern nulling capability. The proposed deceptive jammer produces delayed versions of the intercepted signals to create false targets with multiple ranges to confuse the opponent’s radar system. The novel mathematical model is proposed whose effectiveness is verified through several simulation results for different numbers of ranges, directions, and antenna elements.
Social Networking Services (SNS) have gained immense popularity in developing countries like Indi... more Social Networking Services (SNS) have gained immense popularity in developing countries like India, where digital natives are actively communicating on these platforms. Understanding the interaction between technology systems and digital natives, and proposing guidelines and recommendations for the development of better systems is highly valuable. Prior research examining users’ motivations and actual usage of photo tagging systems is limited, and predominately focused on Flickr and adult users. In order to understand in detail why, how, and with whom users tag digital photos on Facebook, a qualitative essaybased exploratory study is organized with 67 digital natives in India. The study aims to build understanding of the various gratifications, motivations, experiences, and practices associated with Facebook photo tagging, focusing on technologically savvy Indian digital natives. Our results reveal that photo tagging practices by digital natives vary substantially, especially among ...
BACKGROUND Online debates surrounding face masks as a precautionary measure against COVID-19 pand... more BACKGROUND Online debates surrounding face masks as a precautionary measure against COVID-19 pandemic have been raging on social media platforms like Twitter. Users against or in favor of masks have be vocal in sharing their opinions about the masks wearing, practices, and consequences. Through a social network analysis (SNA), we unearth the important contributors to the debate on Twitter surrounding pro and anti-masks. OBJECTIVE The aim of this study is to develop an understanding of the content and influencers on Twitter related to anti-mask and pro-mask debates. METHODS In this study 18,000 tweets related to keywords that were either pro mask and anti-mask from 12th December 2020, to 18th December 2020, and 18,000 tweets from 9th of December to the 18th of December 2020. The two datasets were analysed using social network analysis in Gephi, meanwhile NodeXL was used to produce network metrics and identify the key users, websites, and content within the data. RESULTS Discussions f...
Each year, significant investment of time and resources is made to improve diversity within engin... more Each year, significant investment of time and resources is made to improve diversity within engineering across a range of federal and state agencies, private/not-for-profit organizations, and foundations. In spite of decades of investments, efforts have not yielded desired returns - participation by minorities continues to lag at a time when STEM workforce requirements are increasing. In recent years a new stream of data has emerged - online social networks, including Twitter, Facebook, and Instagram - that act as a key sensor of social behavior and attitudes of the public. Almost 87% of the American population now participates in some form of social media activity. Consequently, social networking sites have become powerful indicators of social action and social media data has shown significant promise for studying many issues including public health communication, political campaign, humanitarian crisis, and, activism. We argue that social media data can likewise be leveraged to be...
Social media provides a mechanism for people to engage with social causes across a range of issue... more Social media provides a mechanism for people to engage with social causes across a range of issues. It also provides a strategic tool to those looking to advance a cause to exchange, promote or publicize their ideas. In such instances, AI can be either an asset if used appropriately or a barrier. One of the key issues for a workforce diversity campaign is to understand in real-time who is participating - specifically, whether the participants are individuals or organizations, and in case of individuals, whether they are male or female. In this paper, we present a study to demonstrate a case for AI for social good that develops a model to infer in real-time the different user types participating in a cause-driven hashtag campaign on Twitter, ILookLikeAnEngineer (ILLAE). A generic framework is devised to classify a Twitter user into three classes: organization, male and female in a real-time manner. The framework is tested against two datasets (ILLAE and a general dataset) and outperf...
Social media provides a mechanism for people to engage with social causes across a range of issue... more Social media provides a mechanism for people to engage with social causes across a range of issues. It also provides a strategic tool to those looking to advance a cause to exchange, promote or publicize their ideas. In such instances, AI can be either an asset if used appropriately or a barrier. One of the key issues for a workforce diversity campaign is to understand in real-time who is participating - specifically, whether the participants are individuals or organizations, and in case of individuals, whether they are male or female. In this paper, we present a study to demonstrate a case for AI for social good that develops a model to infer in real-time the different user types participating in a cause-driven hashtag campaign on Twitter, ILookLikeAnEngineer (ILLAE). A generic framework is devised to classify a Twitter user into three classes: organization, male and female in a real-time manner. The framework is tested against two datasets (ILLAE and a general dataset) and outperf...
Social Networking Services (SNS) have gained immense popularity in developing countries like Indi... more Social Networking Services (SNS) have gained immense popularity in developing countries like India, where digital natives are actively communicating on these platforms. Understanding the interaction between technology systems and digital natives, and proposing guidelines and recommendations for the development of better systems is highly valuable. Prior research examining users’ motivations and actual usage of photo tagging systems is limited, and predominately focused on Flickr and adult users. In order to understand in detail why, how, and with whom users tag digital photos on Facebook, a qualitative essaybased exploratory study is organized with 67 digital natives in India. The study aims to build understanding of the various gratifications, motivations, experiences, and practices associated with Facebook photo tagging, focusing on technologically savvy Indian digital natives. Our results reveal that photo tagging practices by digital natives vary substantially, especially among ...
The novel settings provided by social media facilitate users to seek and share information on a w... more The novel settings provided by social media facilitate users to seek and share information on a wide array of subjects, including healthcare and wellness. Analyzing health-related opinions and discussions on these platforms complement traditional public health surveillance systems to support timely and effective interventions. This study aims to characterize the HIV-related conversations on Twitter by identifying the prevalent topics and the key events and actors involved in these discussions. Through Twitter API, we collected tweets containing the hashtag #HIV for a one-year period. After pre-processing the collected data, we conducted engagement analysis, temporal analysis, and topic modeling algorithm on the analytical sample (n = 122,807). Tweets by HIV/AIDS/LGBTQ activists and physicians received the highest level of engagement. An upsurge in tweet volume and engagement was observed during global and local events such as World Aids Day and HIV/AIDS awareness and testing days fo...
The International Arab Journal of Information Technology
With the advancement in wireless communication technology, the ease of accessibility and increasi... more With the advancement in wireless communication technology, the ease of accessibility and increasing coverage area is a major challenge for service providers. Network densification through Small cell Base Stations (SBS) integration in Heterogeneous Networks (HetNets) promises to improve network performance for cell edge users. Since providing wired backhaul for small cells is not cost effective or practical, the third-Generation Partnership Project (3GPP) has developed architecture for self-backhaul known as Integrated Access and Backhaul (IAB) for Fifth Generation (5G). This allows for Main Base Station (MBS) resources to be shared between SBS and MBS users. However, fair and efficient division of MBS resources remains a problem to be addressed. We develop a novel transmit antenna selection/partitioning technique for taking advantage of IAB 5G standard for Massive Multiple Input Multiple Output (MIMO) HetNets. Transmit antenna resources are divided among access for MBS users and for...
Introduction The availability of a variety of e-cigarettes flavors is one of the frequently cited... more Introduction The availability of a variety of e-cigarettes flavors is one of the frequently cited reasons for their adoption. An active stream of discussion about flavoring can be observed online. Analyzing these real-time conversations offers nuanced insights into key factors related to the adoption of flavors, subsequently supporting public health interventions. Methods Google’s BERT, a state-of-the-art deep learning method was employed to model the first sentiment corpus on JUUL flavors. BERT, which is pre-trained with the complete English Wikipedia was fine-tuned by integrating a classification model, with human labeled Tweets, as training data. A collection of 30 075 Tweets about JUUL flavors was classified into positive and negative sentiments. Finally, using topic models, we identify and grouped thematic areas into positive and negative Tweets. Results With an average of 89% cross-validation precision for classifying Tweets, the fine-tuned BERT model classified 24 114 Tweets ...
Deceptive jamming is a popular electronic countermeasure (ECM) technique that generates false tar... more Deceptive jamming is a popular electronic countermeasure (ECM) technique that generates false targets to confuse opponent surveillance radars. This work presents a novel approach for hiding the actual target while producing multiple false targets at the same time against frequency diverse array (FDA) radar. For this purpose, the modified FDA radar is assumed to be mounted on the actual aircraft. It intercepts the opponent’s radar signals and transmits back to place nulls in the radiation pattern at the desired range and direction to exploit FDA radar’s range-dependent pattern nulling capability. The proposed deceptive jammer produces delayed versions of the intercepted signals to create false targets with multiple ranges to confuse the opponent’s radar system. The novel mathematical model is proposed whose effectiveness is verified through several simulation results for different numbers of ranges, directions, and antenna elements.
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