ABSTRACT
As society grows increasingly more online with each passing year, the problem of cyberbullying becomes more and more prominent, with such incidents having the capacity to negatively impact mental health in a major way, especially among children and teenagers. The proposed approach builds on our previous work that established multi-modal detection of cyberbullying on Twitter, and restructures the multi-modal approach by incorporating social media features such as time-related features and social network information. As a result, the new models reach a classification accuracy between 94.4% and 94.6%, from the previous accuracy of 93%. The proposed new approach affirms the use of context-based data in addition to more directly-related features when analyzing cyberbullying and other interactions with promising improvements. We believe that this work contributes significantly to the study of cyberbullying detection, which is an imminent problem with growing importance in the post-COVID society. © 2022 IEEE.
ABSTRACT
In the past decade, the gaming industry has seen a sharp rise in popularity, particularly in mobile gaming, and these numbers have only increased with the recent COVID-19 pandemic. Given the amount of user information being collected and shared by these gaming apps as well as the demographics of its users such as minors, it is critical to examine these apps' privacy vulnerabilities. In this study, we reviewed and analyzed 20 popular gaming apps' privacy policies and evaluated their explicit privacy protections or lack thereof. In particular, we examined if any specific privacy protections are provided to vulnerable groups like children and teenagers. Results found that although these gaming apps have privacy protections listed in their policies, only a few of them explicitly identify individual's consent and choice. Also, most of the privacy protections on minors like children and teenagers provided by these gaming apps are only at a basic level. Results from this study can provide guidance to both app users and app developers on the measures that each app is already taking on privacy protections, as well as identifying the vulnerabilities and potential privacy risks that currently exist. Furthermore, it can provide guidance for implementing appropriate privacy policies to protect users' personal data. © 2022 IEEE.
ABSTRACT
Privacy concerns around sharing personal health information are frequently cited as hindering COVID-19 contact tracing app adoption. We conducted a nationally representative survey of 304 adults in the United States to investigate their attitudes towards sharing two types of COVID-19 health status (COVID-19 Diagnosis, Exposure to COVID-19) with three different audiences (Anyone, Frequent Contacts, Occasional Contacts). Using the Internet User's Information Privacy Concern (IUIPC) scale, we were able to identify the effect of different types of privacy concerns on sharing this information with various audiences. We found that privacy concerns around data Collection predicted lower willingness to share either type of health status to all of these audiences. However, desire for Control and for Awareness of data practices increased willingness to share health information with certain audiences. We discuss the implications of our findings. © 2022 Owner/Author.
ABSTRACT
Weibo is a widely used social media platform showing all kinds of information related to the COVID-19 pandemic promptly in China. Official media and private media are two typical types of media on Weibo. Due to the different characteristics of these two media types, in the context of public health emergencies, it is worth exploring whether there are differences in the users' interactive behavior with information from these two types of media. This is of great significance to the integration and development of these two types of media.This study obtained data on the interaction behaviors of Weibo users with posts published by the two media types at various stages of the pandemic. Statistical analyses have confirmed significant differences in interaction behavior data between users and these two media types. In future research, based on the findings of this study, we will investigate the reasons behind these differences to provide relevant guidelines and suggestions for the release of different media in public health emergencies by conducting a deep dive analysis of user reviews.
ABSTRACT
Coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Since its first being reported in December 2019, COVID-19 has spread quickly around the world, and becomes a global pandemic. Previous information sources have a number of problems when providing COVID-19 information web services. First, the information from government or traditional media (i.e., TV and newspaper) is not frequently updated. Second, different layers of the government (state and federal government) may provide contradictory information. Also, there are many rumours spread on social media, which makes it difficult for people to know who and what to trust. Finally, the current information about COVID-19 is fragmented. It takes effort for people to aggregate the information they need to see from different places. © 2022 IEEE.
ABSTRACT
The sudden outbreak of COVID-19 has greatly affected the development of all industries, and the development of many enterprises has been severely impacted. In the context of epidemic prevention and control, the Internet has brought new development space for enterprise marketing, so more and more enterprises begin to enter the field of online marketing. With the continuous progress of Internet technology and the deepening of informatization, China's big data industry has made qualitative progress. The traditional marketing model cannot meet the needs of the increasingly fierce market competition. By applying big data technology to network marketing, enterprises can dig deeply into user information and formulate corresponding marketing strategies based on users' preferences, behavior patterns and shopping habits, so as to realize precise marketing and improve their economic benefits by mining potential customers. However, there are also some problems in the process of using big data technology to move towards precision, such as serious homogenization, low application level, and privacy security issues. Only by solving these problems can enterprises use big data to achieve higher quality development. © 2022 IEEE.
ABSTRACT
Since early 2020, the COVID-19 pandemic has been significantly changing people’s daily lives as social activities are limited to slow down the spread of the novel coronavirus. New technologies, especially mobiles apps, have been widely applied to help with reducing the spread of the pandemic. However, although these apps bring many benefits, it also raises privacy issues given the amount of user information being collected and shared. The goal of this study is to understand individuals’ attitudes towards the privacy concerns on using COVID-19 apps, and their expectations on the privacy protections. By conducting the survey and collecting responses, results found that majority of the participants expressed privacy concerns on COVID-19 apps, and participants with different socioeconomic status may have different levels of willingness to use the app. Results from this study not only provide guidance for the government and app service providers on the implementation of appropriate safeguards, but also address on the needs of privacy protections for the vulnerable groups. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
In the Philippines, contact-tracing is done in the conventional method where people fill-up health-declaration forms. Proper physical distancing is not followed, especially in public places. This study is focused on concerns involving the conventional contact tracing and physical distancing in Pamantasan ng Cabuyao. Developed using modified incremental-prototyping methodology. The objective is to develop module device with ranging position, triggered when one-meter distance is compromised and physical distancing notification. Included a web-based application interface for contact-tracing where the administrator can update the status and registration of the users. Utilized block-chain technology as storage for the users' information. The device is developmentally-designed, implemented and evaluated. Based on the series of testing, the device provides notification through blinking light, and set-off to exchange identifications. Users' information is secured through the Block-chain. When a user is reported to be COVID-19 positive, all the users who have been in contact, will be alerted via text message. © 2021 IEEE.
ABSTRACT
The purpose of this paper is to study the changing trend of Chinese Internet users' attitude towards tourism under the influence of COVID-19, and to explore the value of tourism development and change in the stage of normalization of COVID-19. This research obtained 870, 000 user comments by crawler on the topic of "tourism"from Zhihu, China's largest online QA community, and classified 12 first-level topics by exploring the topics in user comments based on LDA model. In addition, this research utilized the SnowNLP model to make emotion analysis on each comment, and compared the trend of users' attention as well as emotion on tourism-related topics in months from 2019 to 2020. It is found that the attention to tourism in online communities has increased due to COVID-19;the fluctuation of attention to each tourism-related topic is closely related to the progress of COVID-19 and the promulgation of related policies. Users' emotion tendency and attention fluctuation in each topic show a high degree of consistency. Based on this, this paper puts forward suggestions including stabilizing the tourism industry structure and vigorously developing online tourism and IP consumption. © 2021 IEEE.
ABSTRACT
Due to the widespread of COVID-19, online conferencing turns into the most popular application that connects people all over the world. The race between platforms in terms of quality and utilities becomes more intense than ever. However, such virtual/online conferencing applications are vulnerable to multiple attacks. Among them, privacy-related issues have not been taken seriously, leading to the problem of infringing upon users’ confidentiality and privacy. This paper is designed to provide a pragmatic model that applies cryptography technology to online conferencing to protect users’ information and guarantee the service quality of the online conferencing after integration. © 2021, Springer Nature Singapore Pte Ltd.