ACM Journal on Computing and Sustainable Societies最新文献

{"title":"Wearable Technology Insights: Unveiling Physiological Responses During Three Different Socially Anxious Activities","authors":"N. K. Sahu, Snehil Gupta, Haroon Lone","doi":"10.1145/3663671","DOIUrl":"https://doi.org/10.1145/3663671","url":null,"abstract":"Wearable technology holds promise for monitoring and managing Social Anxiety Disorder (SAD), yet the absence of clear biomarkers specific to SAD hampers its effectiveness. This paper explores this issue by presenting a study investigating variances in heart rate, heart rate variability, and skin conductance between socially anxious and non-anxious individuals. One hundred eleven non-clinical student participants participated in groups of three in three anxiety-provoking activities (i.e., speech, group discussion, and interview) in a controlled lab-based study. During the study, electrocardiogram (ECG) and electrodermal activity (EDA) signals were captured via on-body electrodes. During data analysis, participants were divided into four groups based on their self-reported anxiety level (“None”, “mild”, “moderate”, and “severe”). Between-group analysis shows that discriminating ECG features (i.e., HR and MeanNN) could identify anxious individuals during anxiety-provoking activities, while EDA could not. Moreover, the discriminating ECG features improved the classification accuracy of anxious and non-anxious individuals in different machine-learning techniques. The findings need to be further scrutinized in real-world settings for the generalizability of the results.","PeriodicalId":486506,"journal":{"name":"ACM Journal on Computing and Sustainable Societies","volume":" 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140997152","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}

{"title":"On Disused Connected Devices: Understanding Disuse, ‘Holding On’ and Barriers to Circularity","authors":"Susan Lechelt, Katerina Gorkovenko, Chris Speed","doi":"10.1145/3651171","DOIUrl":"https://doi.org/10.1145/3651171","url":null,"abstract":"In this paper, we explore the complex phenomena behind why people ‘hold on’ to disused connected devices, focusing especially on differences between ‘traditional’ smartphones and computers, and newer categories of smart home devices, wearables and single-function Internet of Things (IoT) devices. We investigate why and in what contexts different categories of connected devices become disused by their owners; what owners value about their disused devices; and what they perceive to be the barriers to adopting circular practices, for example by fixing, recycling or reusing them. Our contribution is to provide a descriptive account of how functional, sentimental and other values associated with devices shape owners’ perceptions and attitudes toward their ‘end of life’, for an expanded range of connected products. By highlighting how perceptions of concepts including convenience, ownership and wastefulness mediate how owners approach the ‘end of life’ of a device, we map the barriers for device owners to engage in more circular practices and highlight opportunities to address them through design. Our study replicates previous findings in the domain, as well as extending them, contributing how the design of modern IoT devices leads to new barriers, opportunities, and considerations for more circular design.\u0000 Sustainability, Circular Economy, Internet of Things, IoT, Sustainable HCI, Sustainable Interaction Design, Planned Obsolescence, E-waste","PeriodicalId":486506,"journal":{"name":"ACM Journal on Computing and Sustainable Societies","volume":"27 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140252344","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}

{"title":"Analyzing the Energy Usage of a Community and the Benefits of Energy Storage","authors":"John Wamburu, Stephen Lee, Srinivasan Iyengar, David Irwin, Prashant J. Shenoy","doi":"10.1145/3637209","DOIUrl":"https://doi.org/10.1145/3637209","url":null,"abstract":"Understanding the energy usage of a community is crucial for policymaking, energy planning, and achieving sustainable development. The advent of the smart grid has made is feasible to gather fine-grain energy usage data at large-scales, providing us with new opportunities to understand demand patterns at different spatial and temporal scales. In this paper, we conduct a large-scale empirical study of energy usage of 14,849 residential and commercial energy consumers from a small city in the United States. We conduct a wide ranging analysis of energy usage at multiple granularities—citywide, transformer-level, and individual home levels. In doing so, we demonstrate how city-wide smart meter datasets can answer a variety of questions on energy consumption, such as the impact of weather on energy usage. For example, we show that extreme weather events significantly increase energy usage, e.g., by 36% and 11.5% on hot summer and cold winter days, respectively. As another example, we show 19.2% of transformers in the grid get overloaded during peak load periods. Finally, we evaluate the impact of incorporating varying amounts of energy storage within the distribution grid and the impact such deployments will have on the peak demand patterns seen by the grid as well as the ability to reduce overloads seen by distribution transformers during peak periods.","PeriodicalId":486506,"journal":{"name":"ACM Journal on Computing and Sustainable Societies","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138997938","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}

{"title":"Hate Speech Detection in Limited Data Contexts using Synthetic Data Generation","authors":"Aman Khullar, Daniel Nkemelu, Cuong V. Nguyen, Michael L. Best","doi":"10.1145/3625679","DOIUrl":"https://doi.org/10.1145/3625679","url":null,"abstract":"A growing body of work has focused on text classification methods for detecting the increasing amount of hate speech posted online. This progress has been limited to only a select number of highly-resourced languages causing detection systems to either under-perform or not exist in limited data contexts. This is majorly caused by a lack of training data which is expensive to collect and curate in these settings. In this work, we propose a data augmentation approach that addresses the problem of lack of data for online hate speech detection in limited data contexts using synthetic data generation techniques. Given a handful of hate speech examples in a high-resource language such as English, we present three methods to synthesize new examples of hate speech data in a target language that retains the hate sentiment in the original examples but transfers the hate targets. We apply our approach to generate training data for hate speech classification tasks in Hindi and Vietnamese. Our findings show that a model trained on synthetic data performs comparably to, and in some cases outperforms, a model trained only on the samples available in the target domain. This method can be adopted to bootstrap hate speech detection models from scratch in limited data contexts. As the growth of social media within these contexts continues to outstrip response efforts, this work furthers our capacities for detection, understanding, and response to hate speech. Disclaimer: This work contains terms that are offensive and hateful. These, however, cannot be avoided due to the nature of the work.","PeriodicalId":486506,"journal":{"name":"ACM Journal on Computing and Sustainable Societies","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136012610","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}

{"title":"Community and Facility Health Information System Integration in Malawi: A Comparison of Machine Learning and Probabilistic Record Linkage Methods","authors":"Anna Dixon, Limbani Thengo, Emmanuel Kitsao, Kondwani Matiya, Mourice Barasa, Revelation Nyirongo, Jennifer Muli, Funny Kamanga, Chiyembekezo Kachimanga, Fabien Munyaneza, Phillip Ngari, Henry Makungwa, Jones Chimpukuso, Mercy Amulele, Elijah Karari, Simon Mbae","doi":"10.1145/3624773","DOIUrl":"https://doi.org/10.1145/3624773","url":null,"abstract":"research-article Free Access Share on Community and Facility Health Information System Integration in Malawi: A Comparison of Machine Learning and Probabilistic Record Linkage MethodsJust Accepted Authors: Anna Dixon Medic, USA Medic, USASearch about this author , Limbani Thengo Partners In Health, Malawi Partners In Health, MalawiSearch about this author , Emmanuel Kitsao Medic, Kenya Medic, KenyaSearch about this author , Kondwani Matiya Partners In Health, Malawi Partners In Health, MalawiSearch about this author , Mourice Barasa Medic, Kenya Medic, KenyaSearch about this author , Revelation Nyirongo Partners In Health, Malawi Partners In Health, MalawiSearch about this author , Jennifer Muli Medic, Kenya Medic, KenyaSearch about this author , Funny Kamanga Partners In Health, Malawi Partners In Health, MalawiSearch about this author , Chiyembekezo Kachimanga Partners In Health, Malawi Partners In Health, MalawiSearch about this author , Fabien Munyaneza Partners In Health, Malawi Partners In Health, MalawiSearch about this author , Phillip Ngari Medic, Kenya Medic, KenyaSearch about this author , Henry Makungwa Partners In Health, Malawi Partners In Health, MalawiSearch about this author , Jones Chimpukuso Partners In Health, Malawi Partners In Health, MalawiSearch about this author , Mercy Amulele Medic, Kenya Medic, KenyaSearch about this author , Elijah Karari Medic, Kenya Medic, KenyaSearch about this author , Simon Mbae Medic, Kenya Medic, KenyaSearch about this author Authors Info & Claims ACM Journal on Computing and Sustainable SocietiesAccepted on June 2023https://doi.org/10.1145/3624773Published:12 October 2023Publication History 0citation0DownloadsMetricsTotal Citations0Total Downloads0Last 12 Months0Last 6 weeks0 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF","PeriodicalId":486506,"journal":{"name":"ACM Journal on Computing and Sustainable Societies","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136013314","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}

{"title":"To Reply or to Quote: Comparing Conversational Framing Strategies on Twitter","authors":"Himanshu Zade, Spencer Williams, Theresa T. Tran, Christina Smith, Sukrit Venkatagiri, Gary Hsieh, Kate Starbird","doi":"10.1145/3625680","DOIUrl":"https://doi.org/10.1145/3625680","url":null,"abstract":"Social media platform affordances allow users to interact with content and with each other in diverse ways. For example, on Twitter 1 , users can like, reply, retweet, or quote another tweet. Though it’s clear that these different features allow various types of interactions, open questions remain about how these different affordances shape the conversations. We examine how two similar, but distinct conversational features on Twitter — specifically reply vs. quote — are used differently. Focusing on the polarized discourse around Robert Mueller’s congressional testimony in July 2019, we look at how these features are employed in conversations between politically aligned and opposed accounts. We use a mixed methods approach, employing grounded qualitative analysis to identify the different conversational and framing strategies salient in that discourse and then quantitatively analyzing how those techniques differed across the different features and political alignments. Our research (1) demonstrates that the quote feature is more often used to broadcast and reply is more often used to reframe the conversation; (2) identifies the different framing strategies that emerge through the use of these features when engaging with politically aligned vs. opposed accounts; (3) discusses how reply and quote features may be re-designed to reduce the adversarial tone of polarized conversations on Twitter-like platforms.","PeriodicalId":486506,"journal":{"name":"ACM Journal on Computing and Sustainable Societies","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135094113","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}

{"title":"A Characterization of Land-use Changes in the Proximity of Mining Sites in India","authors":"Shivani A Mehta, Mayur Solanki, Aaditeshwar Seth","doi":"10.1145/3624774","DOIUrl":"https://doi.org/10.1145/3624774","url":null,"abstract":"For a growing economy like India, most of its energy resources are obtained through extractive processes such as mining of coal and other minerals. Mining can however have many negative social and ecological impacts if it is not well regulated. Illegal mining or inadequate reclamation of abandoned mines can amplify these impacts, emphasizing the need to develop methods that can monitor changes in the land-use patterns in and around mining sites. We develop a method using machine learning on freely available satellite data to monitor the extent of mines, and augment it with outputs from land use and land cover classification, deforestation detection, and PM2.5 particulate matter estimation from remote sensing data to track land-use and ecological changes taking place in the proximity of mining sites. We provide evaluation results of our mining delineation classifier, a feasibility check of this suite of tools to monitor mining areas over a period of four years, and a temporal characterization study over 628 mines in India that were granted a clearance for operations during the period 2006 to 2012. We further use this suite of monitoring tools to compare socio-economic development and health indicators across mining and non-mining areas, across various states in India, to study whether extractive processes of mining benefit the immediate population in their neighbourhood.","PeriodicalId":486506,"journal":{"name":"ACM Journal on Computing and Sustainable Societies","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135536660","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}

{"title":"On the Frontline During the Covid-19 Pandemic: Gender Inequality and Experiences of Healthcare Workers in Pakistan","authors":"Rukhshan Haroon, Ayesha Naeem, Priya Fatima Sajjad, Zartash Afzal Uzmi","doi":"10.1145/3616862","DOIUrl":"https://doi.org/10.1145/3616862","url":null,"abstract":"This mixed methods study investigates the experiences of healthcare workers (HCWs) along gender lines during the Covid-19 pandemic in Lahore, the second most populous city in Pakistan. In-person semi-structured interviews ( n =62) and researcher-administered surveys ( n =631) were conducted with doctors and nurses in five private and public hospitals. The findings reveal that male and female HCWs shared experiences related to increased working hours, psychological burdens, and adverse financial impacts. However, female HCWs struggled more than male HCWs, as their responsibilities at home and in the workplace increased. Additionally, more female HCWs than their male peers reported experiencing occupational stress due to transportation issues, working during pregnancy, and discriminatory attitudes of the patients toward them. Building on the results from our study, we propose several technological and policy initiatives that can be adopted by governments and organizations, especially in countries like Pakistan, where women account for most of the healthcare workforce but continue to bear a heavier burden when balancing work and family.","PeriodicalId":486506,"journal":{"name":"ACM Journal on Computing and Sustainable Societies","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136152954","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}

{"title":"“What’s the Point of Having this Conversation?”: From a Telephone Crisis Helpline in Bangladesh to the Decolonization of Mental Health Services","authors":"Ananya Bhattacharjee, Sharifa Sultana, Mohammad Ruhul Amin, Yeshim Iqbal, Syed Ishtiaque Ahmed","doi":"10.1145/3616381","DOIUrl":"https://doi.org/10.1145/3616381","url":null,"abstract":"Most of the HCI work on mental health is based on the Western metaphysical definition of mind that is less applicable outside the West. This paper focuses on this issue and critically examines “Kaan Pete Roi” (KPR), a suicide prevention and emotional support helpline in Bangladesh, through an interview study with 20 participants. We find that KPR’s service, grounded in the ‘befriending’ model – originating from the UK and emphasizing non-judgmental active listening without offering direct advice – often struggles to ensure callers’ safety, provide long-term support, and protect volunteers from harassment and distress. We argue that such failures are often rooted in some foundational ideas of the UK-born ‘befriending’ model that underpins the service. Building on Enrique Dussel’s decolonial philosophy, we argue that ‘befriending’ model and its underpinning Western metaphysical ideation of mind carry a colonial impulse, and discuss how community-based approaches may better address the mental health problems in the Global South.","PeriodicalId":486506,"journal":{"name":"ACM Journal on Computing and Sustainable Societies","volume":"189 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135154332","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}

{"title":"A Friend in Need is a Friend Indeed: Investigating the Quality of Training Data from Peers for Auto-generating Empathetic Textual Responses to Non-Sensitive Posts in a Cohort of College Students","authors":"Ravi Sharma, Jamshidbek Mirzakhalov, Pratool Bharti, Raj Goyal, Trine Schmidt, Sriram Chellappan","doi":"10.1145/3616382","DOIUrl":"https://doi.org/10.1145/3616382","url":null,"abstract":"Towards providing personalized care, digital mental-wellness apps today ask questions to learn about subjects. However, not all subjects using these apps will have mood problems, so they do not need follow-up questions. In this study, we investigate an alternate mechanism to handle such non-sensitive posts (i.e., those not indicating mood problems) in college settings. To do so, we generate and use training data provided by a cohort of peer college students so that responses to non-sensitive posts are contextual, emotionally aware, and empathetic while also being terminal (not asking follow-up questions). Using data from a real mental-wellness app used by students, we identify that AI models trained with our peer-provided dataset generate desirable responses to non-sensitive posts, while models trained with state-of-the-art (Facebook’s) Empathetic Dataset yields responses that ask many follow-up questions, hence giving a perception of being intrusive. We believe that mental wellness apps today must not assume that any subject using these apps has mood problems. Perceptions of intrusiveness (i.e., apps asking many questions) must be a factor in design. We also believe that peer students can provide rich and reliable training datasets for college mental wellness apps, a topic that is not yet explored.","PeriodicalId":486506,"journal":{"name":"ACM Journal on Computing and Sustainable Societies","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135308317","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}