An Accessible Web CAPTCHA Design for Visually Impaired Users

In the realm of computing, CAPTCHAs are used to determine if a user engaging with a system is a person or a bot. The most common CAPTCHAs are visual in nature, requiring users to recognize images comprising distorted characters or objects. For people with visual impairments, audio CAPTCHAs are accessible alternatives to standard visual CAPTCHAs. Users are required to enter or say the words in an audio-clip when using Audio CAPTCHAs. However, this approach is time-consuming and vulnerable to machine learning algorithms, since automated speech recognition (ASR) systems could eventually understand the content of audio with the improvement of the technique. While adding background noise may deceive ASR systems temporarily, it may cause people to have difficulties de- ciphering the information, thus reducing usability. To address this, we designed a more secure and accessible web CAPTCHA based on the capabilities of people with visually impairments, obviating the need for sight via the use of audio and movement, while also using object detection techniques to enhance the accessibility of the CAPTCHA

Answering Twitter Questions: a Model for Recommending Answerers through Social Collaboration

International audienceIn this paper, we specifically consider the challenging task of solving a question posted on Twitter. The latter generally remains unanswered and most of the replies, if any, are only from members of the questioner's neighborhood. As outlined in previous work related to community Q&A, we believe that question-answering is a collaborative process and that the relevant answer to a question post is an aggregation of answer nuggets posted by a group of relevant users. Thus, the problem of identifying the relevant answer turns into the problem of identifying the right group of users who would provide useful answers and would possibly be willing to collaborate together in the long-term. Accordingly, we present a novel method, called CRAQ, that is built on the collaboration paradigm and formulated as a group entropy optimization problem. To optimize the quality of the group, an information gain measure is used to select the most likely " informative " users according to topical and collaboration likelihood predictive features. Crowd-based experiments performed on two crisis-related Twitter datasets demonstrate the effectiveness of our collaborative-based answering approach

Crowd-powered systems

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 217-237).Crowd-powered systems combine computation with human intelligence, drawn from large groups of people connecting and coordinating online. These hybrid systems enable applications and experiences that neither crowds nor computation could support alone. Unfortunately, crowd work is error-prone and slow, making it difficult to incorporate crowds as first-order building blocks in software systems. I introduce computational techniques that decompose complex tasks into simpler, verifiable steps to improve quality, and optimize work to return results in seconds. These techniques develop crowdsourcing as a platform so that it is reliable and responsive enough to be used in interactive systems. This thesis develops these ideas through a series of crowd-powered systems. The first, Soylent, is a word processor that uses paid micro-contributions to aid writing tasks such as text shortening and proofreading. Using Soylent is like having access to an entire editorial staff as you write. The second system, Adrenaline, is a camera that uses crowds to help amateur photographers capture the exact right moment for a photo. It finds the best smile and catches subjects in mid-air jumps, all in realtime. Moving beyond generic knowledge and paid crowds, I introduce techniques to motivate a social network that has specific expertise, and techniques to data mine crowd activity traces in support of a large number of uncommon user goals. These systems point to a future where social and crowd intelligence are central elements of interaction, software, and computation.by Michael Scott Bernstein.Ph.D

Search delegation, synthesists and expertise on social media

Background. Social media often adds a layer of intermediation between sources and information consumer, with users outsourcing some of the information work to others. Social media “synthesists” have been identified as a group of volunteer information providers fulfilling this role.Approach. Through a review of evidence from philosophy, information science and knowledge management, this paper explores the implications of cognitive outsourcing, presents quality standards for synthesis and asks how well synthesists meet these. In the process, the role of intermediary is discussed, along with the non-specialist status of the synthesist.Results. Findings show that social media synthesists fulfil a useful role and that their importance in terms of knowledge translation is clear. While their synthesis quality may fall far short of LIS standards, there are a number of ways that some quality issues can be addressed, including the involvement of the information profession itself on the same social platforms.Contribution. Through a comparison of synthesis best practice with current informal information behaviour on social media, the paper draws attention to quality issues and new opportunities to address them. This represents an attempt to identify ways to bridge formal and emerging, informal information markets

Internet Ecologies of New Mothers: Trust, Variety and Strategies for Managing Diverse Information Sources

New parents are faced with the challenge of quickly acquiring a new base of knowledge, while simultaneously navigating a significant life change. While both new mothers and fathers experience new and unique parental demands, their early caregiving challenges differ and new mothers often search for different types of support and information online. We here present findings from an exploratory interview study of how new first-time mothers navigate online resources as they transition into parenthood. We find that many parenting tasks are supported by a variety of resources, which are often used in combination to accomplish a task. We also found that variety in sources was often valued over general source credibility, and new mothers relied on their own ability to filter information to assess how much to trust information. We also provide more general insight into the methods individuals used to gain domain knowledge in a completely new area

Avances en Interacción Humano-Computadora

Crowdsourced content creation like articles or slogans can be powered by crowds of volunteers or workers from paid task markets. Volunteers often have expertise and are intrinsically motivated, but are a limited resource, and are not always reliably available. On the other hand, paid crowd workers are reliably available, can be guided to produce high-quality content, but cost money. How can these different populations of crowd workers be leveraged together to power cost-effective yet high-quality crowdpowered content-creation systems? To answer this question, we need to understand the strengths and weaknesses of each. We conducted an online study where we hired paid crowd workers and recruited volunteers from social media to complete three content creation tasks for three real-world non-profit organizations that focus on empowering women. These tasks ranged in complexity from simply generating keywords or slogans to creating a draft biographical article. Our results show that paid crowds completed work and structured content following editorial guidelines more effectively. However, volunteer crowds provide content that is more original. Based on the findings, we suggest that crowdpowered content-creation systems could gain the best of both worlds by leveraging volunteers to scaffold the direction that original content should take; while having paid crowd workers structure content and prepare it for real world use.Avances en Interacción Humano computadorafile:///C:/Users/Propietario/Downloads/65-13-135-3-10-20210201.pd

Is there a Doctor in the Crowd? Diagnosis Needed! (for less than $5)

We investigate the feasibility of crowd-based medical diagnosis by posting medical cases on a variety of crowdsourcing platforms: general and specialized volunteer question answering sites, and pay-based Mechanical Turk (MTurk) and oDesk. To assess the crowd’s ability to diagnose cases of varying difficulty, three sets of medical cases are considered. While volunteer channels proved ineffective for us, we discuss design limitations and opportunities for improvement. In contrast, Mechanical Turk workers without medical training not only correctly diagnosed easy cases, but also a previously unsolved case from CrowdMed involving extensive patient details. Likely due to varying expertise, MTurk workers and oDesk health professionals also differed in their willingness to provide uncertain diagnoses, diagnosis rationales, and reliance on personal experience with a disease to diagnose it.ye

Remote synchronous crowd support in challenging sports events

Social support is a most powerful expression of human beings. It can make humans overcome barriers that seem impossible. Research shows that athletes, who are supported through being cheered on during events, perform better. However, up until recently, little could be done to cheer athletes during races unless supporters were physically present at the event. We investigate ways in which remote online spectators can support athletes in real-time. Is the support from remote spectators effective? How can we design systems for real-time support and what factors influence their effectiveness? To research this, we iteratively design online crowd interfaces, mobile applications, and devices that allow athletes to communicate with distributed spectators during sport activities. Athletes are able to broadcast their live performance to spectators through locative and biometric data sharing. Concurrently, remote spectators support the athletes by clicking a cheer button that instantly makes the athletes aware that a crowd is following their performance. We then conduct a series of investigations during multiple sport events, using different support modalities and diverse crowds. Results indicate that remote crowd support does motivate the athletes by making the athletes aware that they are being supported. More interestingly, if we categorise supporters into close relatives, acquaintances and unknown spectators, the most effective support seems to be that of acquaintances. This work also provides design guidelines for researchers and designers of remote crowd support systems

Systems for Managing Work-Related Transitions

Peoples' work lives have become ever-populated with transitions across tasks, devices, and environments. Despite their ubiquitous nature, managing transitions across these three domains has remained a significant challenge. Current systems and interfaces for managing transitions have explored approaches that allow users to track work-related information or automatically capture or infer context, but do little to support user autonomy at its fullest. In this dissertation, we present three studies that support the goal of designing and understanding systems for managing work-related transitions. Our inquiry is motivated by the notion that people lack the ability to continue or discontinue their work at the level they wish to do so. We scope our research to information work settings, and we use our three studies to generate novel insights about how empowering peoples' ability to engage with their work can mitigate the challenges of managing work-related transitions. We first introduce and study Mercury, a system that mitigates programmers' challenges in transitioning across devices and environments by enabling their ability to continue work on-the-go. Mercury orchestrates programmers' work practices by providing them with a series of auto-generated microtasks on their mobile device based on the current state of their source code. Tasks in Mercury are designed so that they can be completed quickly without the need for additional context, making them suitable to address during brief moments of downtime. When users complete microtasks on-the-go, Mercury calculates file changes and integrates them into the user's codebase to support task resumption. We then introduce SwitchBot, a conversational system that mitigates the challenges in discontinuing work during the transition between home and the workplace. SwitchBot's design philosophy is centered on assisting information workers in detaching from and reattaching with their work through brief conversations before the start and end of the workday. By design, SwitchBot's detachment and reattachment dialogues inquire about users' task-related goals or user's emotion-related goals. We evaluated SwitchBot with an emphasis on understanding how the system and its two dialogues uniquely affected information workers' ability to detach from and later reattach with their work. Following our study of Mercury and SwitchBot, we present findings from an interview study with crowdworkers aimed at understanding the work-related transitions they experience in their work practice from the perspective of tools. We characterize the tooling observed in crowdworkers' work practices and identified three types of "fragmentation" that are motivated by tooling in the practice. Our study highlights several distinctions between traditional and contemporary information work settings and lays a foundation for future systems that aid next-generation information workers in managing work-related transitions. We conclude by outlining this dissertation's contributions and future research directions