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1. Predicting Facebook sentiments towards research

   https://doi.org/10.1016/j.nlp.2023.100010  

   Shahzad, Murtuza ; Freeman, Cole ; Rahimi, Mona ; Alhoori, Hamed ( June 2023 , Natural Language Processing Journal)

   Social media platforms provide users with various ways of interacting with each other, such as commenting, reacting to posts, sharing content, and uploading pictures. Facebook is one of the most popular platforms, and its users frequently share and reshare posts, including research articles. Moreover, the reactions feature on Facebook allows users to express their feelings towards the content they view, providing valuable data for analysis. This study aims to predict the emotional impact of Facebook posts relating to research articles. We collected data on Facebook posts related to various scientific research domains, including Health Sciences, Social Sciences, Dentistry, Arts, and Humanities. We observed Facebook users’ reactions towards research articles and posts and found that ‘Like’ reactions were the most common. We also noticed that research articles from the Dentistry research domain received a lot of ‘Haha’ reactions. We used machine learning models to predict the sentiment of Facebook posts related to research articles. We used features such as the research article’s title sentiment, abstract sentiment, abstract length, author count, and research domain to build the models. We used five classifiers: Random Forest, Decision Tree, K-Nearest Neighbors, Logistic Regression, and Naïve Bayes. The models were evaluated using accuracy, precision, recall, and F-1 score metrics. The Random Forest classifier was the best model for two- and three-class labels, achieving accuracy measures of 86% and 66%, respectively. We also evaluated the feature importance for the Random Forest model and found that the sentiment of the research article’s title is crucial in predicting the sentiment of the Facebook post. This study has substantial implications for public engagement in science-related messages. The emotional reactions of Facebook users towards research articles and posts can provide valuable insights into public engagement in science, and predicting the emotional impact of Facebook posts related to research articles can help researchers understand how the public perceives scientific research. The findings of the study can aid researchers in effectively communicating their research and engaging the public in scientific discourse. 

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2. An Investigation on the Portrayal of Blue Whale Challenge on YouTube and Twitter

   https://doi.org/10.1177/1071181319631179  

   Khasawneh, Amro ; Chalil Madathil, Kapil ; Dixon, Emma ; Wisniewski, Pamela ; Zinzow, Heidi ; Roth, Rebecca ( November 2019 , Proceedings of the Human Factors and Ergonomics Society Annual Meeting)

   Introduction Social media has created opportunities for children to gather social support online (Blackwell et al., 2016; Gonzales, 2017; Jackson, Bailey, & Foucault Welles, 2018; Khasawneh, Rogers, Bertrand, Madathil, & Gramopadhye, 2019; Ponathil, Agnisarman, Khasawneh, Narasimha, & Madathil, 2017). However, social media also has the potential to expose children and adolescents to undesirable behaviors. Research showed that social media can be used to harass, discriminate (Fritz & Gonzales, 2018), dox (Wood, Rose, & Thompson, 2018), and socially disenfranchise children (Page, Wisniewski, Knijnenburg, & Namara, 2018). Other research proposes that social media use might be correlated to the significant increase in suicide rates and depressive symptoms among children and adolescents in the past ten years (Mitchell, Wells, Priebe, & Ybarra, 2014). Evidence based research suggests that suicidal and unwanted behaviors can be promulgated through social contagion effects, which model, normalize, and reinforce self-harming behavior (Hilton, 2017). These harmful behaviors and social contagion effects may occur more frequently through repetitive exposure and modelling via social media, especially when such content goes “viral” (Hilton, 2017). One example of viral self-harming behavior that has generated significant media attention is the Blue Whale Challenge (BWC). The hearsay about this challenge is that individuals at all ages are persuaded to participate in self-harm and eventually kill themselves (Mukhra, Baryah, Krishan, & Kanchan, 2017). Research is needed specifically concerning BWC ethical concerns, the effects the game may have on teenagers, and potential governmental interventions. To address this gap in the literature, the current study uses qualitative and content analysis research techniques to illustrate the risk of self-harm and suicide contagion through the portrayal of BWC on YouTube and Twitter Posts. The purpose of this study is to analyze the portrayal of BWC on YouTube and Twitter in order to identify the themes that are presented on YouTube and Twitter posts that share and discuss BWC. In addition, we want to explore to what extent are YouTube videos compliant with safe and effective suicide messaging guidelines proposed by the Suicide Prevention Resource Center (SPRC). Method Two social media websites were used to gather the data: 60 videos and 1,112 comments from YouTube and 150 posts from Twitter. The common themes of the YouTube videos, comments on those videos, and the Twitter posts were identified using grounded, thematic content analysis on the collected data (Padgett, 2001). Three codebooks were built, one for each type of data. The data for each site were analyzed, and the common themes were identified. A deductive coding analysis was conducted on the YouTube videos based on the nine SPRC safe and effective messaging guidelines (Suicide Prevention Resource Center, 2006). The analysis explored the number of videos that violated these guidelines and which guidelines were violated the most. The inter-rater reliabilities between the coders ranged from 0.61 – 0.81 based on Cohen’s kappa. Then the coders conducted consensus coding. Results & Findings Three common themes were identified among all the posts in the three social media platforms included in this study. The first theme included posts where social media users were trying to raise awareness and warning parents about this dangerous phenomenon in order to reduce the risk of any potential participation in BWC. This was the most common theme in the videos and posts. Additionally, the posts claimed that there are more than 100 people who have played BWC worldwide and provided detailed description of what each individual did while playing the game. These videos also described the tasks and different names of the game. Only few videos provided recommendations to teenagers who might be playing or thinking of playing the game and fewer videos mentioned that the provided statistics were not confirmed by reliable sources. The second theme included posts of people that either criticized the teenagers who participated in BWC or made fun of them for a couple of reasons: they agreed with the purpose of BWC of “cleaning the society of people with mental issues,” or they misunderstood why teenagers participate in these kind of challenges, such as thinking they mainly participate due to peer pressure or to “show off”. The last theme we identified was that most of these users tend to speak in detail about someone who already participated in BWC. These videos and posts provided information about their demographics and interviews with their parents or acquaintances, who also provide more details about the participant’s personal life. The evaluation of the videos based on the SPRC safe messaging guidelines showed that 37% of the YouTube videos met fewer than 3 of the 9 safe messaging guidelines. Around 50% of them met only 4 to 6 of the guidelines, while the remaining 13% met 7 or more of the guidelines. Discussion This study is the first to systematically investigate the quality, portrayal, and reach of BWC on social media. Based on our findings from the emerging themes and the evaluation of the SPRC safe messaging guidelines we suggest that these videos could contribute to the spread of these deadly challenges (or suicide in general since the game might be a hoax) instead of raising awareness. Our suggestion is parallel with similar studies conducted on the portrait of suicide in traditional media (Fekete & Macsai, 1990; Fekete & Schmidtke, 1995). Most posts on social media romanticized people who have died by following this challenge, and younger vulnerable teens may see the victims as role models, leading them to end their lives in the same way (Fekete & Schmidtke, 1995). The videos presented statistics about the number of suicides believed to be related to this challenge in a way that made suicide seem common (Cialdini, 2003). In addition, the videos presented extensive personal information about the people who have died by suicide while playing the BWC. These videos also provided detailed descriptions of the final task, including pictures of self-harm, material that may encourage vulnerable teens to consider ending their lives and provide them with methods on how to do so (Fekete & Macsai, 1990). On the other hand, these videos both failed to emphasize prevention by highlighting effective treatments for mental health problems and failed to encourage teenagers with mental health problems to seek help and providing information on where to find it. YouTube and Twitter are capable of influencing a large number of teenagers (Khasawneh, Ponathil, Firat Ozkan, & Chalil Madathil, 2018; Pater & Mynatt, 2017). We suggest that it is urgent to monitor social media posts related to BWC and similar self-harm challenges (e.g., the Momo Challenge). Additionally, the SPRC should properly educate social media users, particularly those with more influence (e.g., celebrities) on elements that boost negative contagion effects. While the veracity of these challenges is doubted by some, posting about the challenges in unsafe manners can contribute to contagion regardless of the challlenges’ true nature. 

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3. Modeling Aesthetics and Emotions in Visual Content: From Vincent van Gogh to Robotics and Vision

   Wang, James Z. ( October 2020 , Proceedings of the Joint Workshop on Aesthetic and Technical Quality Assessment of Multimedia and Media Analytics for Societal Trends, in conjunction with the ACM International Conference on Multimedia)

   null (Ed.)

   As inborn characteristics, humans possess the ability to judge visual aesthetics, feel the emotions from the environment, and comprehend others’ emotional expressions. Many exciting applications become possible if robots or computers can be empowered with similar capabilities. Modeling aesthetics, evoked emotions, and emotional expressions automatically in unconstrained situations, however, is daunting due to the lack of a full understanding of the relationship between low-level visual content and high-level aesthetics or emotional expressions. With the growing availability of data, it is possible to tackle these problems using machine learning and statistical modeling approaches. In the talk, I provide an overview of our research in the last two decades on data-driven analyses of visual artworks and digital visual content for modeling aesthetics and emotions. First, I discuss our analyses of styles in visual artworks. Art historians have long observed the highly characteristic brushstroke styles of Vincent van Gogh and have relied on discerning these styles for authenticating and dating his works. In our work, we compared van Gogh with his contemporaries by statistically analyzing a massive set of automatically extracted brushstrokes. A novel extraction method is developed by exploiting an integration of edge detection and clustering-based segmentation. Evidence substantiates that van Gogh’s brushstrokes are strongly rhythmic. Next, I describe an effort to model the aesthetic and emotional characteristics in visual contents such as photographs. By taking a data-driven approach, using the Internet as the data source, we show that computers can be trained to recognize various characteristics that are highly relevant to aesthetics and emotions. Future computer systems equipped with such capabilities are expected to help millions of users in unimagined ways. Finally, I highlight our research on automated recognition of bodily expression of emotion. We propose a scalable and reliable crowdsourcing approach for collecting in-the-wild perceived emotion data for computers to learn to recognize the body language of humans. Comprehensive statistical analysis revealed many interesting insights from the dataset. A system to model the emotional expressions based on bodily movements, named ARBEE (Automated Recognition of Bodily Expression of Emotion), has also been developed and evaluated. 

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4. Reversing Privacy Risks: Strict Limitations on the Use of Communications Metadata and Telemetry Information

   Landau, Susan ; Vargas Leon, Patricia ( October 2023 , Colorado technology law journal)

   In this paper, we examine private-sector collection and use of metadata and telemetry information and provide three main contributions: First, we lay out the extent to which “non-content”—the hidden parts of Internet communications (aspects the user does not explicitly enter) and telemetry—are highly revelatory of personal behavior. We show that, privacy policies notwithstanding, users rarely know that the metadata and telemetry information is being collected and almost never know the uses to which it is being put. Second, we show that consumers, even if they knew the uses to which this type of personal information were being put, lack effective means to control the use of this type of data. The standard tool of notice-and-choice has well known problems, including the user’s lack of information with which to make a choice; and then, even if the user had sufficient information, doing so is not practical.49 These are greatly exacerbated by the nature of the interchanges for communications metadata and telemetry information. Each new transmission—each click on an internal link on a webpage, for example—may carry different implications for a user in terms of privacy. The current regimen, notice-and-choice, presents a completely unworkable set of requests for a user, who could well be responding many times a minute regarding whether to allow the use of metadata beyond the purposes of content delivery and display. This is especially the case for telemetry, where the ability to understand both present and future use of the data provided from the sensors requires a deeper understanding of what information these devices can provide than anyone but a trained engineer would know. Third, while there has been academic and industry research on telemetry’s use, there has been little exploration of the policy and legal implications stemming from that use. We provide this factor, while at the same time addressing the closely related issues raised by industry’s use of communications metadata to track user interests and behavior 

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5. User vs. Engineer: Student Perceptions of Responsibility in Social Media

   Stepback, L. ; Hwang, M. H. ; Claussen, S. ; Leonardo, Y. ( June 2023 , ASEE Annual Conference & Exposition)

   Engineers are responsible to many stakeholders, including the public and their employer. One such responsibility is considering and accounting for the potential impacts and risks associated with a technology that they create. A relatively new, and potentially risky, technology that has been on the rise over the past two decades is social media. The advent of social media, such as Facebook and Twitter, and its integration into our daily lives raises questions about the duty engineers bear for its responsible usage and design versus the responsibilities users have as they use the technology. This paper analyzes qualitative interview data from a study on engineering students’ perceptions of engineering ethics and social responsibility to answer the following research question: In what ways do students change (or not change) how they talk about engineers’ social and professional responsibilities to the technologies they create when framed in the context of social media? Our findings show that mentioning social media as a specific application of engineering ethics rendered visible the relationship between engineers, users, and technology that students then utilized to address the broader question about engineers’ responsibility to the technologies they create. In this study, a total of 33 students from three U.S. universities were interviewed longitudinally, once in the first year of their degree and again in the fourth year. In the interviews, the students were asked about their views on the social and professional duties engineers have for the technologies they create, framed in the context of social media. Analysis of student responses involved open and axial coding of relevant interview portions performed by two researchers to identify common themes and longitudinal changes between student interviews. These themes included: communication between the engineer and user, collective responsibility, benefits to society, high quality engineering, and misinformation. While students typically maintained elements of their views across both interviews, it was also common to see students change their responses to include new themes or exclude themes present in their initial interview. The students tended to believe that engineers have a responsibility to think through potential uses (or misuses) of their technology, but also believe that the users share some responsibility to use the technology appropriately. When social media was mentioned specifically, some students believed that the users were entirely responsible for how the technology is used, occasionally contradicting their views of engineering ethics when probed without the context of social media. This paper highlights the central tension between user responsibility and engineer responsibility. By illuminating students’ views, it will support educators in opening a dialogue with their students about who is ultimately responsible for the design and use of new technologies. 

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