User Profiles for Facilitating Conversations with Locked-In Users

The loss of communication is one of the most profound disabilities a human being can experience, inhibiting social contact and complicating medical and personal care. Locked-in patients are paralyzed and unable to speak, but cognitively intact. Developments in biometric technology provide non-muscular channels of control and provide opportunities to restore some communication for people with little or no muscle movement. Although these biometric devices have been effective, the input rate is very slow for the requirements of interactive communication. Prediction techniques increase the speed of communication in assistive technology. However, the user’s context (time of day, location, presence of conversational partners, user’s interests, etc.) can be included to make the selection of desired phrases or utterances easier and faster. This research presents an approach to developing user profiles for locked-in users. The profiles can be used to enhance the speed and accuracy of conversation by reducing the selection space for conversational topics. An empirical study that simulates the application of user profiles demonstrates how they can be used to improve the speed and accuracy of conversation in severely disabled users relying on augmentative and assistive communication devices

Twitter: A Professional Development and Community of Practice Tool for Teachers

This article shows how a group of language teachers use Twitter as a tool for continuous professional development through the #MFLtwitterati hashtag. Based on data collected through a survey (n=116) and interviews (n=11), it describes how this collective of teachers use the hashtag and evaluates the impact of their Twitter network on their teaching practices. The results show that most users try the suggestions and ideas that they find on this network, which have a positive impact on their teaching. Finally, the article assesses whether the hashtag users can be described as a community of practice

Towards Predicting Control of a Brain-Computer Interface

Individuals suffering from locked-in syndrome are completely paralyzed and unable to speak but otherwise cognitively intact. Traditional assistive technology is ineffective for this population of users due to the physical nature of input devices. Brain-computer and biometric interfaces offer users with severe motor disabilities a non-muscular input channel for communication and control, but require that users be able to harness their appropriate electrophysiological responses for effective use of the interface. There is currently no formalized process for determining a user’s aptitude for control of various biometric interfaces without testing on an actual system. This study presents how basic information captured about users may be used to predict their control of a brain-computer interface that is based on electrical variations in the motor cortex region of the brain. Based on data from 55 able-bodied users, we found that the interaction of age and daily average amount of hand-and-arm movement by individuals correlates to their ability in brain- computer interface control. This research may be expanded into a more robust model linking individual characteristics and control of various biometric interfaces

Individual-Technology Fit: Matching Individual Characteristics and Features of Biometric Interface Technologies with Performance

Abstract INDIVIDUAL-TECHNOLOGY FIT: MATCHING INDIVIDUAL CHARACTERISTICS AND FEATURES OF BIOMETRIC INTERFACE TECHNOLOGIES WITH PERFORMANCE By ADRIANE B. RANDOLPH MAY 2007 Committee Chair: Dr. Melody Moore Jackson Major Department: Computer Information Systems The term biometric literally means “to measure the body”, and has recently been associated with physiological measures commonly used for personal verification and security applications. In this work, biometric describes physiological measures that may be used for non-muscularly controlled computer applications, such as brain-computer interfaces. Biometric interface technology is generally targeted for users with severe motor disabilities which may last long-term due to illness or injury or short-term due to temporary environmental conditions. Performance with a biometric interface can vary widely across users depending upon many factors ranging from health to experience. Unfortunately, there is no systematic method for pairing users with biometric interface technologies to achieve the best performance. The current methods to accommodate users through trial-and-error result in the loss of valuable time and resources as users sometimes have diminishing abilities or suffer from terminal illnesses. This dissertation presents a framework and methodology that links user characteristics and features of biometric interface technologies with performance, thus expediting the technology-fit process. The contributions include an outline of the underlying components of capturing and representing individual user characteristics and the impact on the performance of basic interaction tasks using a methodology called biometric user profiling. In addition, this work describes a methodology for objectively measuring an individual’s ability to control a specific biometric interface technology such as one based on measures of galvanic skin response or neural activity. Finally, this work incorporates these concepts into a new individual-technology fit framework for biometric interface technologies stemming from literature on task-technology fit. Key words: user profiles, biometric user profiling, biometric interfaces, fit, individual-technology fit, galvanic skin response, functional near-infrared, brain-computer interfac

When users control the algorithms: Values expressed in practices on the twitter platform

Recent interest in ethical AI has brought a slew of values, including fairness, into conversations about technology design. Research in the area of algorithmic fairness tends to be rooted in questions of distribution that can be subject to precise formalism and technical implementation. We seek to expand this conversation to include the experiences of people subject to algorithmic classification and decision-making. By examining tweets about the “Twitter algorithm” we consider the wide range of concerns and desires Twitter users express. We find a concern with fairness (narrowly construed) is present, particularly in the ways users complain that the platform enacts a political bias against conservatives. However, we find another important category of concern, evident in attempts to exert control over the algorithm. Twitter users who seek control do so for a variety of reasons, many well justified. We argue for the need for better and clearer definitions of what constitutes legitimate and illegitimate control over algorithmic processes and to consider support for users who wish to enact their own collective choices

Instant Messaging privacy in the clouds

Instant messaging are applications that allow spontaneous communication between two or more people, enabling the relationship between them regardless of the distance that separates them. Also, social network like Facebook used to maintain contact current or old friends, to publish and view photos, to allow a closer relationship between the contacts and private instant messaging is including in its structure. Instant messaging applications are placed in the cloud to facilitate the access to users from any workstation resulting in better cooperation and exchange of information between users. Since the instant messenger needs an internet connection, there are disadvantages of privacy and security, given the risk that messages are sent to be read by strangers. This paper proposes the inclusion of a privacy mechanism to protect information sent or received and allow the personalization according to the user preferences in instant messaging in the cloud

Timescales of Massive Human Entrainment

The past two decades have seen an upsurge of interest in the collective behaviors of complex systems composed of many agents entrained to each other and to external events. In this paper, we extend concepts of entrainment to the dynamics of human collective attention. We conducted a detailed investigation of the unfolding of human entrainment - as expressed by the content and patterns of hundreds of thousands of messages on Twitter - during the 2012 US presidential debates. By time locking these data sources, we quantify the impact of the unfolding debate on human attention. We show that collective social behavior covaries second-by-second to the interactional dynamics of the debates: A candidate speaking induces rapid increases in mentions of his name on social media and decreases in mentions of the other candidate. Moreover, interruptions by an interlocutor increase the attention received. We also highlight a distinct time scale for the impact of salient moments in the debate: Mentions in social media start within 5-10 seconds after the moment; peak at approximately one minute; and slowly decay in a consistent fashion across well-known events during the debates. Finally, we show that public attention after an initial burst slowly decays through the course of the debates. Thus we demonstrate that large-scale human entrainment may hold across a number of distinct scales, in an exquisitely time-locked fashion. The methods and results pave the way for careful study of the dynamics and mechanisms of large-scale human entrainment.Comment: 20 pages, 7 figures, 6 tables, 4 supplementary figures. 2nd version revised according to peer reviewers' comments: more detailed explanation of the methods, and grounding of the hypothese

From scene to screen: the challenges and opportunities that digital platforms pose for HIV prevention work with MSM

This article draws upon data from Reaching Out Online, a collaborative research project that explored the need for, and development of, a digital health outreach service for gay, bisexual and MSM men in London and Brighton, UK. It identifies the challenges that commercial hook-up apps and other digitally-based dating and sex services pose for conventional forms of gay men’s health promotion. It then moves to explore the opportunities that these same services offer for health promotion teams. Chiefly, the discussion highlights the potential that commercial platforms offer to peer educators in terms of reaching local cohorts of men, together with the constraints placed upon this form of outreach as a result of the commercial imperatives that underpin these digital services