Drivers and Challenges of Wearable Devices Use: Content Analysis of Online Users Reviews

With recent advancements in wearable device technologies, there is still a need to investigate drivers and challenges associated with the use of these devices. Following a content analysis approach, this study leverages recent “found large-scale” data to better understand the drivers and challenges that affect the adoption and use of such devices. Analyzing a total of 16,717 online reviews about wearable devices, the findings emphasized the importance of various functionalities (perceived usefulness), appeal, and a number of device design features as the most prominent drivers, while concerns about quality, credibility, and perceived value as potential challenges to wearable adoption and continued use. The findings could inform theoretical models for technology adoption and continued use and can also provide guidance to the design and development of wearable devices

Systematically Monitoring Social Media: the case of the German federal election 2017

It is a considerable task to collect digital trace data at a large scale and at the same time adhere to established academic standards. In the context of political communication, important challenges are (1) defining the social media accounts and posts relevant to the campaign (content validity), (2) operationalizing the venues where relevant social media activity takes place (construct validity), (3) capturing all of the relevant social media activity (reliability), and (4) sharing as much data as possible for reuse and replication (objectivity). This project by GESIS - Leibniz Institute for the Social Sciences and the E-Democracy Program of the University of Koblenz-Landau conducted such an effort. We concentrated on the two social media networks of most political relevance, Facebook and Twitter.Comment: PID: http://nbn-resolving.de/urn:nbn:de:0168-ssoar-56149-4, GESIS Papers 2018|

From social computing to digital transformation: the advent of the social machine / Da computação social à transformação digital: o advento da máquina social

A internet suas inovações mudaram novos paradigmas e estratégias de crescimento de processos, métodos, sistemas organizacionais e sociais, transformando em transformações e digitais. Um dos paradigmas é os problemas de máquinas que integram elementos computacionais e sociais software, fazendo com que a complexidade de operações e serviços pautados seja pela sociedade e pela sociedade sejam adaptados à prática de resolução de problemas sociais. A forma como o software foi desenvolvido, implantado e usado mudou ao longo do tempo como o software foi desenvolvido, implantado e usado ao mesmo tempo que o mesmo tempo de relacionamento e data similar anteriormente conhecido.Este estudo como conseqüências das transformações modernas tem importância, a partir da existência da transformação social da transformação social, a partir da existência da transformação social da transformação social, a partir da existência da transformação social e da transformação social, a partir da existência da transformação social da transformação digital. Esta pesquisa social pensada como sistemas de informação, computação social, máquinas, transformação digital e empreendedorismo. A metodologia utilizada nesta pesquisa foi baseada na Design Science Research (DSR) que utilizou uma abordagem metodológica teórica-conceitual baseada em revisão humana entre literatura, observando a evolução das técnicas, inovação e negócios.O processo de transformação digital tem a ver com as mudanças comportamentais projetadas pela inovação das Tecnologias de Informação e Comunicação (TICs) e da estratégia empresarial. O advento da Máquina Social gerou um processo de revolução de paradigmas, 

Building an innovation discontinuance model : the case of twitter

This dissertation seeks to extend Everett Rogers’s Diffusion of Innovations theory by examining social media users’ post-adoption behavior. Despite the rapid growth of social networking sites (SNSs), the rate of user discontinuance is staggering. Keeping users active and engaged has always been a crucial issue for SNSs. Prior diffusion research has largely focused on innovation adoption, whereas innovation discontinuance is overlooked. However, innovation discontinuance is a vital facet of the diffusion process. In the real world, only a few innovations become institutionalized while most end up being fads that most users discontinue quickly. While early studies approached discontinuance as a one-time, complete abandonment of an innovation, this study extends the concept by examining two types of discontinuance: intermittent and permanent. Intermittent discontinuers are users who leave an innovation for a break but resume the use at a later time; permanent discontinuers are those who have no intentions to return. This study takes a mixed-methods approach—combining a user survey with computational analyses of “big data” drawn from Twitter—to explore the differences between intermittent and permanent discontinuers in three dimensions: (1) their distinctive characteristics (demographic, behavioral, and psychographic), (2) reasons for discontinuance, and (3) decision processes. The concept of intermittent discontinuance leads to the development of a new post-adoption decision-making model, which accounts for discontinuers’ planned and unplanned readoption behavior. This cyclical, multi-stage model also provides a systematic framework to compare the behavior and cognitive reasoning between intermittent and permanent discontinuers at each phase of the post-adoption cycle. While prior studies employed both qualitative and quantitative research methods to examine discontinuance, few came up with clear and reliable ways to measure the timeframe of discontinuance and users’ reasons for discontinuance. To address the arbitrariness of determining what length of inactivity constitutes intermittent and permanent discontinuance, this study introduces a mathematical approach based on an innovation’s life cycle and its user base. To examine users’ reasons for discontinuance, this study refines and expands Rogers and Shoemaker’s replacement-disenchantment typology—by factors and by discontinuance typologies. While Rogers conceptualized the innovation-diffusion process as an uncertainty reduction process, this study suggests that post-adoption decision-making process is a disturbance-coping mechanism—a temporal settlement of the constant interplay between an innovation’s utilitarian performance and social media exhaustion. Intermittent discontinuance usually occurs due to information overloads. Permanent discontinuance tends to occur due to perceived innovation shortcomings and innovation replacement. This dissertation provides theoretical insights into the temporal instability of an innovation, and why and how an innovation is discarded or discredited. The findings contribute to an adequate comprehension of the entire innovation diffusion process, which also helps SNS providers develop tailor-made retention solutions to re-engage SNS users.Journalis

Politische Maschinen: Maschinelles Lernen für das Verständnis von sozialen Maschinen

This thesis investigates human-algorithm interactions in sociotechnological ecosystems. Specifically, it applies machine learning and statistical methods to uncover political dimensions of algorithmic influence in social media platforms and automated decision making systems. Based on the results, the study discusses the legal, political and ethical consequences of algorithmic implementations.Diese Arbeit untersucht Mensch-Algorithmen-Interaktionen in sozio-technologischen Ökosystemen. Sie wendet maschinelles Lernen und statistische Methoden an, um politische Dimensionen des algorithmischen Einflusses auf Socialen Medien und automatisierten Entscheidungssystemen aufzudecken. Aufgrund der Ergebnisse diskutiert die Studie die rechtlichen, politischen und ethischen Konsequenzen von algorithmischen Anwendungen

Computational social science for the World Wide Web

In this article, we want to introduce the field of computational social science to the intelligent systems community and discuss how this field can help to advance the current state of understanding and engineering social-computational systems on the World Wide Web. Overall, this article makes an argument that computational social science offers a unique range of challenges as well as methods and techniques that can help understand and engineer systems on the World Wide Web