Individual Communication Research Articles

Overview of Tensor-Based Cooperative MIMO Communication Systems—Part 2: Semi-Blind Receivers

Cooperative MIMO communication systems play an important role in the development of future sixth-generation (6G) wireless systems incorporating new technologies such as massive MIMO relay systems, dual-polarized antenna arrays, millimeter-wave communications, and, more recently, communications assisted using intelligent reflecting surfaces (IRSs), and unmanned aerial vehicles (UAVs). In a companion paper, we provided an overview of cooperative communication systems from a tensor modeling perspective. The objective of the present paper is to provide a comprehensive tutorial on semi-blind receivers for MIMO one-way two-hop relay systems, allowing the joint estimation of transmitted symbols and individual communication channels with only a few pilot symbols. After a reminder of some tensor prerequisites, we present an overview of tensor models, with a detailed, unified, and original description of two classes of tensor decomposition frequently used in the design of relay systems, namely nested CPD/PARAFAC and nested Tucker decomposition (TD). Some new variants of nested models are introduced. Uniqueness and identifiability conditions, depending on the algorithm used to estimate the parameters of these models, are established. Two families of algorithms are presented: iterative algorithms based on alternating least squares (ALS) and closed-form solutions using Khatri–Rao and Kronecker factorization methods, which consist of SVD-based rank-one matrix or tensor approximations. In a second part of the paper, the overview of cooperative communication systems is completed before presenting several two-hop relay systems using different codings and configurations in terms of relaying protocol (AF/DF) and channel modeling. The aim of this presentation is firstly to show how these choices lead to different nested tensor models for the signals received at destination. Then, by capitalizing on these models and their correspondence with the generic models studied in the first part, we derive semi-blind receivers to jointly estimate the transmitted symbols and the individual communication channels for each relay system considered. In a third part, extensive Monte Carlo simulation results are presented to compare the performance of relay systems and associated semi-blind receivers in terms of the symbol error rate (SER) and channel estimate normalized mean-square error (NMSE). Their computation time is also compared. Finally, some perspectives are drawn for future research work.

M-MAT Meta: Treatment of Self-Awareness and Language for Individuals With Severe Wernicke's Aphasia.

In this study, we evaluated the feasibility and efficacy of language plus goal management training program for individuals with aphasia. The intervention targeted expressive language, while concurrently integrating tasks designed to improve executive function and error awareness. A single-subject repeated-measures design was utilized to determine whether a combined treatment (Multi-Modal Aphasia Therapy PLUS Goal Management Training [M-MAT Meta]) would be efficacious for individuals with aphasia. This article reports on two participants with severe Wernicke's aphasia, who comprised one of the four dyads of the study. Treatment was administered in a small group setting (N = 2) for 2 hr per day, 3 days per week for 4 weeks. Individual video feedback sessions were conducted once a week. Analysis of outcomes included visual inspection and calculation of Tau-U effect sizes of probed treatment data as well as statistical analysis of standardized language and executive function assessments. Visual inspection indicated improvements in naming and discourse skills, which were maintained at the 1-month follow-up. Both participants' standardized scores indicated a significant decrease in aphasia severity, which was maintained 1 month posttreatment. Error awareness improved for one of the two participants, but this improvement was not maintained. Participants demonstrated increased inhibition of unwanted responses and took longer on the planning and problem-solving time required to complete the assessment, indicating a decrease in impulsivity. The results of this preliminary study suggest that M-MAT Meta may be an effective way to increase self-awareness and communication in individuals with severe Wernicke's aphasia.

Ethical Implications of AI-Driven AAC Systems: Ensuring Inclusivity and Equity in Assistive Technologies

This study investigates the ethical implications of Artificial Intelligence (AI) integration into Augmentative and Alternative Communication (AAC) systems, focusing on inclusivity, accessibility, and data privacy in assistive technologies. AI-driven AAC systems enhance communication for individuals with impairments by offering features like predictive text, speech recognition, and symbol-to-text translation. However, ethical challenges arise as these systems increasingly rely on sensitive user data, which could jeopardize privacy without strict safeguards. Furthermore, limitations in linguistic diversity within AI training data compromise inclusivity, potentially excluding users from varied cultural and linguistic backgrounds. Accessibility also remains an issue, as AI-driven AAC systems are often financially inaccessible for marginalized communities, exacerbating social inequities. Through a comprehensive analysis of current systems, including Proloquo2Go, Tobii Dynavox and Google’s Project Euphonia, this paper evaluates both the advancements and ethical shortcomings in AI-driven AAC technologies. The findings advocate for privacy-preserving AI practices, culturally diverse training datasets, and affordable AAC solutions to foster a more inclusive, accessible, and equitable digital communication environment.

The Communication Performance Analysis of the In Room Dining Division at Hotel “A” as the Basis for the Formation of Organizational Culture

Communication performance and organizational culture are closely related, in the process an individual's communication performance reflects their organization's culture. Every company has its organizational culture, including Hotel “A," which is one of the 5-star international hotels in Jakarta, also experiencing issues with its organizational culture. This study employs descriptive research with a qualitative approach. The method used in this research is interview with employees from the in-room dining division at Hotel “A”, that is a 2 active members of the organization. The research findings reveal problems in the communication performance at Hotel “A”. For instance, in terms of ritual performance, there is a company culture of working overtime. Additionally, in terms of passion performance, the abundance of job tasks in the in-room dining division diminishes the manager's focus, especially for unexperienced leader in a similar divisions. Social performance shows the existence of factions within the organization but with no significant impact on operations. Political performance manifests as a sense of superiority over certain groups (seniority). Lastly, enculturation performance indicates differences in training between staff levels and daily workers, creating clearer disparities. All of these issues stem from the inadequate communication performance in the in-room dining division at Hotel “A”. If left unaddressed, they may lead to demotivation, a decline in work ethic, and feelings of saturation among employees, ultimately impacting the formation of the company's culture. The researcher suggests that management and Human Resources collaborate to address these issues, fostering open communication and welcoming input to establish positive organizational culture.

Applications of Augmented and Virtual Reality in Enhancing Communication for Individuals Who Are Hard of Hearing: A Systematic Review.

This systematic review examines the role of augmented reality (AR) and virtual reality (VR) in enhancing communication for individuals who are hard of hearing. Following Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines, we conducted a comprehensive search across databases including PubMed, WoS, EMBASE, and IEEE. Of the 5,981 records initially identified, 22 studies met our inclusion criteria after screening. Most of these studies (68%) focused on nonverbal communication modalities using tools such as sign language and visual cues, while the remainder focused on verbal communication. A descriptive synthesis was used due to the expected diversity in study characteristics. Our assessment showed a substantial emphasis on educational impacts, speech perception, and cognitive skills development through AR and VR. The reviewed articles provide preliminary evidence on the efficacy of these technologies in teaching sign language, enhancing cognitive skills such as reasoning, and improving speech perception among the deaf or hard of hearing individuals. This review underscores the transformative potential of AR and VR in addressing communication challenges faced by individuals who are hard of hearing, emphasizing the need for further research with diverse, larger sample sizes to investigate these technologies for broader communication support.

When adults with speech-language impairment meet law enforcement: A qualitative analysis of client experiences

IntroductionMembers of law enforcement and the general public who have limited knowledge of persons with communication impairments (PCI) may misinterpret their communication behaviors. Few studies exist about communication between PCI and law enforcement, and data are lacking about the factors that may influence their interactions. Considering this need, we addressed the following research questions: How will PCI describe their attitudes and experiences related to interacting with law enforcement? What individual characteristics may influence these attitudes and experiences? MethodsIn individual semi-structured interviews, we asked 10 adults with speech-language differences (aphasia, dysarthria, or stuttering) to describe their experiences of interacting with members of law enforcement, the communication strategies they would use when interacting with law enforcement, and what they would like members of law enforcement to know about their communication needs. In qualitative analyses, we generated themes from the data. ResultsThree main themes and four subthemes were evident in participant responses. Participant emotions and communication behavior were affected in complex ways during their interactions with a person of authority in uniform. In this sample of PCI, levels of confidence about communicating with strangers were lower for participants with no visible characteristics versus those who exhibited these signs. The participants recommended communication strategies for use by members of law enforcement. ConclusionsThese findings extend the limited literature on this topic to include factors that appear to influence the attitudes and experiences of PCI during their interactions with law enforcement. In clinical application, speech-language pathologists have an important role to play in assisting clients to practice individualized communication strategies for interactions with law enforcement in various contexts. Further research is needed into the perspectives of PCI and the attitudes and experiences of law enforcement when interacting with PCI.

The Share of Data in Maritime Communications is Increasing

Communication is of great importance for the safe and delay-free navigation of ships. Especially life/property safety, navigational warnings, weather forecast reports, storm warnings, navigation maps, etc. Timely transmission of information to ships is only possible with effective maritime communications. In addition, communication is of great importance in making appropriate navigation plans based on the information received from the ships. In recent years, the share of data communication in individual and corporate communications has been increasing. In order to benefit from the great conveniences and opportunities provided by data communication in maritime communication systems, very radical decisions have recently been taken within IMO. These regulations made at the international level paved the way for data communication in close-range maritime communication systems. In line with these regulations, broadband data communication between the ship and the land will begin to be made via VHF devices in the next few years. Another development that will improve broadband data communication in maritime communication systems has been in Near Orbit Satellite systems. The technical features of these systems, the number of which has been increasing in recent years, are extremely suitable for data communication between ship and land. Among these, the Starlink system completes its network in space faster than other satellite systems. It is inevitable that the Starlink system, whose global satellite structure will be completed to a large extent by the end of 2025, will be used to a large extent in data communication between ships and land and between ships with each other. With the use of broadband data feature in the near future, it will be possible for ships to navigate much more safely, efficiently and with a reduced risk of accidents. For this purpose, maritime enterprises, ship personnel and land units must be informed about these developments and their communication infrastructure must be established by taking these systems into consideration.

Painting workshops for people living with dementia as a means of expression and communication: revelations from our elders

Purpose This study aims to explore art workshops for people living with dementia as a process enabling creative expression and fostering communication with others. Design/methodology/approach To enable detailed exploration of the expressive powers of painting and drawing, the authors draw several examples from a series of painting workshops for people living with dementia, which formed part of the PPI for research into experiences of restraint within care. Findings Artwork enabled personal expression, facilitated conversation with others and revealed hidden knowledge and abilities, but also revealed dangers of miscommunication, specifically here related to technological changes and spirituality. Research limitations/implications Individual differences in responses to painting will exist meaning that the specific findings outlined here are unique to individuals and not always generalisable. This follows from the quality of the individual communication that may be enabled by painting, meaning that close attention to each person is both fostered and required. Practical implications Art activities can provide a means to enable deep personal expression and agency in people living with dementia, which can contribute to countering dehumanisation. Social implications Attention to the process of painting can be beneficial in fostering verbal and non-verbal communication with individuals who have difficulties in communication. Attention to cultural issues in care needs to incorporate understanding of spiritual and religious issues and take note of gaps in understanding related to technological as well as cultural changes between generations. Originality/value Much work in this area explores art activities for people living with dementia in terms of beneficial outcomes. This work explores the creative process inherent in painting, drawing upon insights from art theory and providing in-depth individual insights through case studies. Both researchers in this study are artists and the work drew upon their understanding of the processes of painting.

INCREASING THE EFFECTIVENESS OF PHYSICAL TRAINING OF SENIOR STUDENTS THROUGH THE SPORTS CLUB MODEL

The development of the Sports Club model in the system of primary, secondary and high schools will contribute to creating conditions for students to have an environment to develop their physical abilities, develop their individual sports talents, communication and cooperation skills, language skills, etc. In addition, Sports Clubs will be a place to practice, discover and train a source of excellent students to participate in quality sports competitions at all levels, creating a healthy playground for them to avoid social evils at school. Thereby, helping students improve their physical qualities such as strength, speed, endurance, flexibility and dexterity, contributing to their love of sports and improving their health towards becoming healthy citizens to build and protect the country in the future.<p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/soc/0719/a.php" alt="Hit counter" /></p>

Identification of perceived sentences using deep neural networks in EEG

Objetive. Decoding speech from brain activity can enable communication for individuals with speech disorders. Deep neural networks (DNNs) have shown great potential for speech decoding applications. However, the limited availability of large datasets containing neural recordings from speech-impaired subjects poses a challenge. Leveraging data from healthy participants can mitigate this limitation and expedite the development of speech neuroprostheses while minimizing the need for patient-specific training data.Approach. In this study, we collected a substantial dataset consisting of recordings from 56 healthy participants using 64 EEG channels. Multiple neural networks were trained to classify perceived sentences in the Spanish language using subject-independent, mixed-subjects, and fine-tuning approaches. The dataset has been made publicly available to foster further research in this area.Main results. Our results demonstrate a remarkable level of accuracy in distinguishing sentence identity across 30 classes, showcasing the feasibility of training DNNs to decode sentence identity from perceived speech using EEG. Notably, the subject-independent approach rendered accuracy comparable to the mixed-subjects approach, although with higher variability among subjects. Additionally, our fine-tuning approach yielded even higher accuracy, indicating an improved capability to adapt to individual subject characteristics, which enhances performance. This suggests that DNNs have effectively learned to decode universal features of brain activity across individuals while also being adaptable to specific participant data. Furthermore, our analyses indicate that EEGNet and DeepConvNet exhibit comparable performance, outperforming ShallowConvNet for sentence identity decoding. Finally, our Grad-CAM visualization analysis identifies key areas influencing the network's predictions, offering valuable insights into the neural processes underlying language perception and comprehension.Significance. These findings advance our understanding of EEG-based speech perception decoding and hold promise for the development of speech neuroprostheses, particularly in scenarios where subjects cannot provide their own training data.

Neural Signature and Decoding of Unmanned Aerial Vehicle Operators in Emergency Scenarios Using Electroencephalography.

Brain-computer interface (BCI) offers a novel means of communication and control for individuals with disabilities and can also enhance the interactions between humans and machines for the broader population. This paper explores the brain neural signatures of unmanned aerial vehicle (UAV) operators in emergencies and develops an operator's electroencephalography (EEG) signals-based detection method for UAV emergencies. We found regularity characteristics similar to classic event-related potential (ERP) components like visual mismatch negativity (vMMN) and contingent negative variation (CNV). Source analysis revealed a sequential activation of the occipital, temporal, and frontal lobes following the onset of emergencies, corresponding to the processing of attention, emotion, and motor intention triggered by visual stimuli. Furthermore, an online detection system was implemented and tested. Experimental results showed that the system achieved an average accuracy of over 88% in detecting emergencies with a detection latency of 431.95 ms from the emergency onset. This work lays a foundation for understanding the brain activities of operators in emergencies and developing an EEG-based detection method for emergencies to assist UAV operations.

Expanding the scope: multimodal dimensions in aphasia discourse analysis-preliminary findings.

Aphasia, resulting from acquired brain injury, disrupts language processing and usage, significantly impacting individuals' social communication and life participation. Given the limitations of traditional assessments in capturing the nuanced challenges faced by individuals with aphasia, this study seeks to explore the potential benefits of integrating multimodal communication elements into discourse analysis to better capture narrative proficiency in this population. This study examined how incorporating multimodal communication elements (e.g., physical gestures, writing, drawing) into discourse analysis may affect the narrative outcomes of persons with aphasia compared to those observed using methods that exclude multimodal considerations. Participants included individuals with chronic aphasia and age-and education-matched healthy controls who completed a storytelling task-the Bear and the Fly story. Macrolinguistic scores were obtained using verbal-only and multimodal scoring approaches. Additionally, the frequency and type of multimodal communication use during storytelling were examined in relation to aphasia characteristics. Statistical analyses included both within-group and between-group comparisons as well as correlational analyses. Individuals with aphasia scored significantly higher in terms of their macrolinguistic abilities when multimodal scoring was considered compared to verbal-only scoring. Within the aphasia group, there were prominent differences noted in macrolinguistic scores for both fluent and nonfluent aphasia. Specifically, both groups scored higher on Main Concepts when multimodal scoring was considered, with the nonfluent group demonstrating significantly higher Main Concept and total macrolinguistic rubric scores in multimodal scoring compared to verbal scoring on the storytelling task. Additionally, aphasia severity showed moderate positive correlations with total macrolinguistic scores, indicating that individuals with less severe aphasia tended to produce higher quality narratives. Lastly, although persons with aphasia used different types of nonverbal modalities (i.e., drawing, writing), the use of meaning-laden gestures was most predominant during storytelling, emphasizing the importance of multimodal elements in communication for individuals with aphasia. Our preliminary study findings underscore the importance of considering multimodal communication in assessing discourse performance among individuals with aphasia. Tailoring assessment approaches based on aphasia subtypes can provide valuable insights into linguistic abilities and inform targeted intervention strategies for improving communication outcomes.

Real-time detection of spoken speech from unlabeled ECoG signals: A pilot study with an ALS participant.

Brain-Computer Interfaces (BCIs) hold significant promise for restoring communication in individuals with partial or complete loss of the ability to speak due to paralysis from amyotrophic lateral sclerosis (ALS), brainstem stroke, and other neurological disorders. Many of the approaches to speech decoding reported in the BCI literature have required time-aligned target representations to allow successful training - a major challenge when translating such approaches to people who have already lost their voice. In this pilot study, we made a first step toward scenarios in which no ground truth is available. We utilized a graph-based clustering approach to identify temporal segments of speech production from electrocorticographic (ECoG) signals alone. We then used the estimated speech segments to train a voice activity detection (VAD) model using only ECoG signals. We evaluated our approach using held-out open-loop recordings of a single dysarthric clinical trial participant living with ALS, and we compared the resulting performance to previous solutions trained with ground truth acoustic voice recordings. Our approach achieves a median error rate of around 0.5 seconds with respect to the actual spoken speech. Embedded into a real-time BCI, our approach is capable of providing VAD results with a latency of only 10 ms. To the best of our knowledge, our results show for the first time that speech activity can be predicted purely from unlabeled ECoG signals, a crucial step toward individuals who cannot provide this information anymore due to their neurological condition, such as patients with locked-in syndrome. ClinicalTrials.gov, registration number NCT03567213.

Research participant perceptions of personal utility in disclosure of individual research results from genomic analysis.

This article elaborates research participant perspectives on the communication of individual research results from genomic analyses. While most analyses focus on how to communicate results from the perspectives of clinicians or researchers, there is insufficient data on user perspectives and how this information may be used, valued, and interpreted by patients and their families. The concept of personal utility, which considers factors related to quality of life, including on how information may impact the person's future decisions, has been shown to be particularly relevant to understand research participant perspectives and to move beyond clinical and analytic utility factors such as mortality and morbidity. This article draws from qualitative research of research participants awaiting genomic results in the case of sudden cardiac death. Our results show perspectives of personal utility in communication of genomic results, including cognitive, behavioral, and affective outcomes. Cognitive outcomes include gain of information, improved knowledge of etiology and inheritance characteristics, and curiosity for what might be found. Behavioral outcomes include being able to plan life decisions, while affective outcomes include various coping strategies used. We will also discuss the value of knowing negative results and incidental findings from the research participant's perspective. This contribution gives suggestions on best practices to guide genome analysis returns, including incorporating participant wishes on individualized communication at the consent stage; developing relational autonomy approaches; and engaging them throughout the research trajectory.

Teaching patient safety in remote consulting

ABSTRACT A significant proportion of primary care consultations now happen remotely. Although the vast majority occur safely, a recent study highlighted areas of risk which may be compounded by the limited training many GPs have received in remote consulting. To provide safe remote services, consideration needs to be given to adapting practice workflow to optimise remote care. Patients less suitable for remote consulting, either due to disease, extremes of age, disability or for social reasons should be identified and prioritised for face-to-face encounters. Training supports both the development of individual communication skills for remote care, and effective team working. Practice-based group learning events can be used to share experiences, identify resources, and consider the risks in remote care and how they can be mitigated. The paper presents some fictionalised cases, illustrating where patients came to harm, as a result of a remote consultation, and where harm was averted due to actions taken by practice teams. These can be used to support critical thinking and discussion within practice development meetings and tutorials with trainee GPs and other practice staff. Using the paper as a basis for reflection, teaching and action can facilitate the delivery of safer remote care.

ESTRATÉGIAS DA ANÁLISE DO COMPORTAMENTO APLICADA PARA DESENVOLVER A INTERAÇÃO SOCIAL EM CRIANÇAS AUTISTAS

Autism Spectrum Disorder (ASD) has evolved from a psychiatric classification to a neurodevelopmental disorder, reflecting advances in scientific understanding and diagnostic approaches. The DSM-5, with its more sensitive criteria, facilitates early identification of ASD, which is crucial for effective interventions. Applied Behavior Analysis (ABA) is a proven approach for enhancing social skills and reducing problematic behaviors in children with ASD. By employing techniques such as positive reinforcement and modeling, ABA fosters individualized communication and social interaction, providing significant benefits for both children and their families. Integrating playful resources and innovative strategies can complement interventions, promoting greater autonomy and self-awareness in autistic children. Ongoing advancements in ASD diagnosis and treatment, combined with scientific innovation, are essential for improving the quality of life for children and their families.

A Review on Deep Learning Based Sign Language Recognition Translation

Hand posture is often referred to as gesture. It refers to the specific movements and postures that occur when a person utilizes his or her arms. It is one of the earliest and still widely used communication tools. In general, gestures are both dynamic and static. In the process of long-term social practice, gestures are given a variety of specific meanings, has a rich expressive power, the range of motion is extensive when the fingers, wrists, elbows, shoulders, and other joints of the hand are considered. The capacity for flexibility is considerable. Gestures have become a primary means of expression for humans, enabling the conveyance of emotions. In this context, body language occupies a pivotal role. Sign language is defined as the use of hand gestures with or without the use of facial expressions to convey meaning. The combination of hand gestures and facial expressions can be used to imitate images or to represent syllables, which together constitute a certain meaning or word. Sign language is a means of communication for individuals who are deaf or hard of hearing. It is an essential tool for communication, enabling them to express themselves and interact with others in a way that is accessible and understandable. This paper summarizes the deep learning based gesture recognition techniques in recent six years. In recent years, gesture recognition has been in the hot spot, and every year the articles on gesture recognition are constantly updated, so it is evident that a review of the research on gesture recognition is very necessary. This paper also compares and analyzes the existing gesture recognition methods and analyzes their advantages and disadvantages, and puts forward an outlook on the future development.

Stable multiplex networks: definitions and characterizations

Abstract Communication and interaction of individuals in the real world cannot be represented by one-layer networks, and in our paper we use multiplex networks capturing the complexity of their interactions. We define players’ utilities taking into account a multilayer structure of the network by specifying different ways of accounting players’ costs. Using two approaches, we obtain stability conditions for special multilplex structures including all-layer complete, all-layer star with unique or different centers, and all-layer unique networks.

Exploring Barriers Faced by Community Pharmacists in Serving Patients with Disabilities in Saudi Arabia: Recommendations for Enhancing Healthcare Provisions.

A mixed-methods cross-sectional phenomenological study was conducted among community pharmacists in Saudi Arabia between March and April 2022. Both closed- and open-ended questions were utilized to identify themes related to community pharmacists' barriers and experiences when providing care to individuals with disabilities. A total of 40 community pharmacists participated in this study. Among them, 57.5% reported encountering difficulties when caring for patients with disabilities, with 65% indicating a lack of specialized services at their respective community pharmacies. Three major themes emerged from the findings: the need for pharmacist training and awareness, technology-guided methods for overcoming communication barriers, and improving overall pharmacy accessibility. This study reveals a significant gap in the provision of services for patients with disabilities in Saudi Arabia. Addressing physical accessibility, providing targeted training, and leveraging technology can enhance care delivery and promote inclusivity. Further research is warranted to assess the effectiveness of technological solutions and the integration of artificial intelligence in improving communication and patient-centered care for individuals with disabilities.

Timely, Granular, and Actionable: Designing a Social Listening Platform for Public Health 3.0

Every day, patients access and generate online health content through a variety of channels, creating an ever-expanding sea of digital data. At the same time, proponents of public health have recently called for timely, granular, and actionable data to address a range of public health issues, stressing the need for social listening platforms that can identify and compile this valuable data. Yet previous attempts at social listening in healthcare have yielded mixed results, largely because they have failed to incorporate sufficient context to understand the communications they seek to analyze. Guided by activity theory to design HealthSense, we propose a platform for efficiently sensing and gathering data across the web for real-time analysis to support public health outcomes. HealthSense couples theory-guided content analysis and graph propagation with graph neural networks (GNNs) to assess the relevance and credibility of information, as well as intelligently navigate the complex online channel landscape, leading to significant improvements over existing social listening tools. We demonstrate the value of our artifact in gathering information to support two exemplar public health tasks: (1) performing postmarket drug surveillance for adverse reactions and (2) addressing the opioid crisis by monitoring for potent synthetic opioids released into communities. Our results across data, user, and event experiments show that effective design artifacts can enable better outcomes across both automated and human decision-making contexts, making social listening for public health possible, practical, and valuable. Through our design process, we extend activity theory to address the complexities of modern online communication platforms, where information resides not only in the collection of individual communication activities but also in the complex network of interactions among them.