Affordances of social media in collective action: the case of Free Lunch for Children in China

This paper studies the socialised affordances of social media in the processes of collective action, exploring the role of technology in the under‐researched area of civil society. We examine the case of Free Lunch for Children (FL4C), a charitable programme in China based on the microblogging platform, Weibo. Adopting the perspective of affordances‐for‐practice, we draw upon the collective action model to better understand the sociomaterial practices and social processes involving social media, and seek to address the ‘when’ and ‘how’ questions of affordances. The study generates theoretical and practical implications for understanding the role of social media in social transformation.     

What Interactivity Means to the User Essential Insights into and a Scale for Perceived Interactivity

The selection and use of media depend largely on how users perceive such media. A central aspect of the “new media” is their interactivity, but how users perceive this phenomenon has rarely been researched. This study provides an in‐depth investigation into the perception component of interactivity and develops a compact scale for its measurement. According to psychological approaches, practical uses (affordances) – not physical or technical characteristics – guide perception. While existing scales mostly measure whether the “interactive” technical features of devices or websites are noticed, our instrument is based on the affordances that interactivity provides. Consequently, a new research design, the use‐identified meaning, was implemented. This is the first study on interactivity that empirically examines a wide range of Internet‐based services, thus meeting the broad ambit of interactivity. Our results generally validate the existing constructs, which are largely based on technical characteristics, yet provide additional insights into the relevant contexts and the subjective significance of different aspects of interactivity.     

An affordance perspective of enterprise social media and organizational socialization

In response to the challenge of socializing new IT employees, some IT departments are exploring the incorporation of enterprise social media (hereinafter ESM) as an informal organizational socialization tool. Because this is a relatively new phenomenon, little is known about how ESM facilitate employee socialization. In order to contribute to our understanding of how ESM affects employee socialization, this paper invokes a case study to explore how one organization’s implementation of an ESM for its IT new hire program influenced the socialization process and outcomes. To delve deeply into how the ESM influences socialization, we draw upon technology affordance theory to uncover the various first and second-order affordances actualized by different actor groups and the various outcomes resulting from the affordances. We then identify five generative mechanisms – bureaucracy circumvention, executive perspective, personal development, name recognition, and morale booster – that explain how the actualization of different strands of affordances by various groups of users produces eight different outcomes. Our results provide insights into the different affordances made possible by ESM in the context of a new hire socialization program and how these affordances have repercussions beyond those experienced by the individuals using the ESM. The results have important implications for new hire socialization and technology affordance research.     

Perceptions of overuse,underuse, and change of use of a social media site: definition,measurement instrument,and their managerial impacts

Drawing on the person-environment fit model, this study investigates a user’s perceptions towards his/her online contacts’ overuse, underuse, and change of use of a social media site (SMS). A new instrument for measuring these perceptions is introduced. Using depersonalisation and continuance as an example, we test how the relationship between a user and an SMS can be impacted by his/her online contacts’ peculiar usage of the SMS. A survey-based methodology is used to collect data from Facebook users. The data analysis shows that a user is likely to feel estranged from an SMS, if he/she perceives that the website is being overused, underused, or used for non-social purposes by his/her online contacts. The depersonalisation can then have a strong negative effect on the user’s SMS continuance. This study takes the interpersonal influences between users into consideration when investigating a user’s relationship with an SMS. The findings can provide several practical implications for an SMS user retention management.     

Opening organizational learning in crisis management: On the affordances of social media

Research on the role of social media in crisis management has led to a deeper understanding of their affordances. This research, however, is fragmented, with a primary focus on crisis response. We lack a clear conceptualization of the affordances that social media offer by learning from them to prepare strategically for crises. Based on a systematic review of 128 papers, we inductively build a framework of social media affordances for organizational learning in crisis management. We discuss their role and interplay in strategic crisis management, focusing on organizational crisis learning, and outline avenues for future research based on this foundation.     

Combining social media affordances for organising collective action

Social media provide new opportunities for supporting the dynamics of collective action (CA), allowing for the mobilisation of people into debates and involving them in new forms of collective decision making. Although current studies focus on opportunities offered by social media for collective action, there is still a need to deepen the understanding of how social media support the organisation of CA and to study the effects of individual actions performed on social media in complex organisational settings. We here explore how social media are used to manage CA by the Italian political movement Movimento Cinque Stelle, using the concept of affordances as the conceptual framing. Based on the qualitative case analyses, our study contributes to the knowledge base by identifying a typology of nine affordances supporting CA and exploring how the combined actualisations of some affordances of the typology create antecedents of the fundamental processes of CA. On the basis of the study analysis, we suggest a model to describe how social media support CA through affordances, their combinations, and the creation of antecedents and then formulate implications for research and practice.     

Digitally enabled disaster response: the emergence of social media as boundary objects in a flooding disaster

In recent times, social media has been increasingly playing a critical role in response actions following natural catastrophes. From facilitating the recruitment of volunteers during an earthquake to supporting emotional recovery after a hurricane, social media has demonstrated its power in serving as an effective disaster response platform. Based on a case study of Thailand flooding in 2011 – one of the worst flooding disasters in more than 50 years that left the country severely impaired – this paper provides an in‐depth understanding on the emergent roles of social media in disaster response. Employing the perspective of boundary object, we shed light on how different boundary spanning competences of social media emerged in practice to facilitate cross‐boundary response actions during a disaster, with an aim to promote further research in this area. We conclude this paper with guidelines for response agencies and impacted communities to deploy social media for future disaster response.     

Dynamic adaptation of numerical attributes in a user profile

Recommender systems try to help users in their decisions by analyzing and ranking the available alternatives according to their preferences and interests, modeled in user profiles. The discovery and dynamic update of the users’ preferences are key issues in the development of these systems. In this work we propose to use the information provided by a user during his/her interaction with a recommender system to infer his/her preferences over the criteria used to define the decision alternatives. More specifically, this paper pays special attention on how to learn the user’s preferred value in the case of numerical attributes. A methodology to adapt the user profile in a dynamic and automatic way is presented. The adaptations in the profile are performed after each interaction of the user with the system and/or after the system has gathered enough information from several user selections. We have developed a framework for the automatic evaluation of the performance of the adaptation algorithm that permits to analyze the influence of different parameters. The obtained results show that the adaptation algorithm is able to learn a very accurate model of the user preferences after a certain amount of interactions with him/her, even if the preferences change dynamically over time.     

Cyber-volunteering: Social media affordances in fulfilling NGO social missions

Cyber-volunteering behavior through social media is becoming popular among nongovernmental organization (NGO) members. Cyber-volunteering activities have become more aggressive with the availability of social media in recent years. The objective of this paper is to discuss voluntary behavior in fulfilling NGO social missions through social media usage based on affordance theory. There is substantial literature discussing social media affordances in the context of enterprise organization, but there has been less literature discussing the activities of NGOs in social media. Hence, seven key affordances derived from the enterprise organization were used in the context of NGO working behavior, visibility, editability, persistence, virtual collaboration, synthetic representation, individualized, and collective. This research applies a qualitative methodology using semi-structured interviews with 25 NGO members from seven selected Islamic NGOs in Malaysia that are active in different fields of Islamic education. The interviews focus on social media affordances that have influenced the execution of social missions in the NGOs. Data was analyzed using thematic coding based on the seven identified key social media affordances. The results suggest that the social media affordances related to cyber-volunteering are achieved through promoting, training, fundraising, knowledge sharing, and problem-solving activities. These affordances are highly influenced by cyber-volunteering behavior through work culture and personal privacy. The collective, individualized, and visibility affordances are most associated with cyber-volunteering behavior, followed by persistence, virtual collaboration, and editability, and synthetic representation is found to be the least.     

Characterizing users’ check-in activities using their scores in a location-based social network

Analysis of users’ check-ins in location-based social networks (LBSNs, also called GeoSocial Networks), such as Foursquare and Yelp, is essential to understand users’ mobility patterns and behaviors. However, most empirical results of users’ mobility patterns reported in the current literature are based on users’ sampled and nonconsecutive public check-ins. Additionally, such analyses take no account of the noise or false information in the dataset, such as dishonest check-ins created by users. These empirical results may be biased and hence may bring side effects to LBSN services, such as friend and venue recommendations. Foursquare, one of the most popular LBSNs, provides a feature called a user’s score. A user’s score is an aggregate measure computed by the system based on more accurate and complete check-ins of the user. It reflects a snapshot of the user’s temporal and spatial patterns from his/her check-ins. For example, a high user score indicates that the user checked in at many venues regularly or s/he visited a number of new venues. In this paper, we show how a user’s score can be used as an alternative way to investigate the user’s mobility patterns. We first characterize a set of properties from the time series of a user’s consecutive weekly scores. Based on these properties, we identify different types of users by clustering users’ common check-in patterns using non-negative matrix factorization (NMF). We then analyze the correlations between the social features of user clusters and users’ check-in patterns. We present several interesting findings. For example, users with high scores (more mobile) tend to have more friends (more social). Our empirical results demonstrate how to uncover interesting spatio-temporal patterns by utilizing the aggregate measures released by a LBSN service.     

A semantic and social-based collaborative recommendation of friends in social networks

The development of social media technologies has greatly enhanced social interactions. The proliferation of social platforms has generated massive amounts of data and a considerable number of persons join these platforms every day. Therefore, one of the current issues is to facilitate the search for the most appropriate friends for a given user. We focus in this article on the recommendation of users in social networks. We propose a novel approach which combines a user-based collaborative filtering (CF) algorithm with semantic and social recommendations. The semantic dimension suggests the close friends based on the calculation of the similarity between the active user and his friends. The social dimension is based on some social-behavior metrics such as friendship and credibility degree. The novelty of our approach concerns the modeling of the credibility of the user, through his/her trust and commitment in the social network. A social recommender system based on this approach is developed and experiments have been conducted using the Yelp social network. The evaluation results demonstrated that the proposed hybrid approach improves the accuracy of the recommendation compared with the user-based CF algorithm and solves the sparsity and cold start problems.     

A Review of Guidance Approaches in Visual Data Analysis: A Multifocal Perspective

Visual data analysis can be envisioned as a collaboration of the user and the computational system with the aim of completing a given task. Pursuing an effective system‐user integration, in which the system actively helps the user to reach his/her analysis goal has been focus of visualization research for quite some time. However, this problem is still largely unsolved. As a result, users might be overwhelmed by powerful but complex visual analysis systems which also limits their ability to produce insightful results. In this context, guidance is a promising step towards enabling an effective mixed‐initiative collaboration to promote the visual analysis. However, the way how guidance should be put into practice is still to be unravelled. Thus, we conducted a comprehensive literature research and provide an overview of how guidance is tackled by different approaches in visual analysis systems. We distinguish between guidance that is provided by the system to support the user, and guidance that is provided by the user to support the system. By identifying open problems, we highlight promising research directions and point to missing factors that are needed to enable the envisioned human‐computer collaboration, and thus, promote a more effective visual data analysis.     

基于用户QoE的流媒体系统性能测评模型设计

影响流媒体用户服务质量体验QoE(Quality of Experience)的因素有很多,如何对用户QoE进行量化判别是一个复杂的问题。为此,以媒体传输指标MDI为基础,研究了用于测量流媒体用户QoE的基本指标,并提出了相关测量数据的获取方法。以流媒体用户的实际体验质量为依据,提出了一种有效的流媒体系统性能评价模型,该模型为流媒体系统的性能分析和优化调整提供了理论基础,具有广泛的应用价值。     

A user authentication system using back-propagation network

Information security has been a critical issue in the field of information systems. One of the key factors in the security of a computer system is how to identify the authorization of users. Password-based user authentication is widely used to authenticate a legitimate user in the current system. In conventional password-based user authentication schemes, a system has to maintain a password table or verification table which stores the information of users IDs and passwords. Although the one-way hash functions and encryption algorithms are applied to prevent the passwords from being disclosed, the password table or verification table is still vulnerable. In order to solve this problem, in this paper, we apply the technique of back-propagation network instead of the functions of the password table and verification table. Our proposed scheme is useful in solving the security problems that occurred in systems using the password table and verification table. Furthermore, our scheme also allows each user to select a username and password of his/her choice.     

The use of interactive media among today’s youth: Results of a survey

The intensive use of interactive media has led to assertions about the effect of these media on youth. This paper presents a quantitative study on the position of interactive media in young people’s lives. Rather than following the assumption of a homogeneous generation, we investigate the existence of a diversity of user patterns. The research question for this paper: Can patterns be found in the use of interactive media among youth? We answer this question by a survey among Dutch youngsters aged 10–23. Four clusters of interactive media users, namely Traditionalists, Gamers, Networkers and Producers were identified using cluster analysis. Behind these straightforward clusters, a complex whole of user activities can be found. Each cluster shows specific use of and opinions about interactive media. This provides a contextualized understanding of the position of interactive media in the lives of contemporary youth, and a nuanced conceptualization of the ‘Net generation’. This allows for studying the intricate relationship between youth culture, interactive media and learning.     

Digitally enabled affordances for community‐driven environmental movement in rural Malaysia

The immense environmental challenges facing society today have necessitated a research effort toward exploring digitally enabled solutions for environmental problems. Only limited research exists today to inform our understanding on how technology could assist groups of individuals in cultivating collective commitment and engaging in actions for environmental sustainability. By presenting an in‐depth case study of a social media‐enabled grassroots environmental movement in rural Malaysia, this paper aims to illuminate and understand an underresearched phenomenon of community‐driven environmental sustainability. This study makes 2 contributions: (1) we draw on the perspective of technology affordances to shed light on both the enabling power and unintended consequences of social media in the pursuit of environmental sustainability; and on that account, (2) we contribute rich, empirically informed insights toward understanding the underresearched phenomenon of digitally enabled, community‐driven environmental sustainability.     

A motives framework of social media website use: A survey of young Americans

Social media is increasingly important in daily life and is an especially important social interaction mechanism for young people. Although research has been conducted evaluating user types based on motives for using social media, no such framework has been extended to social media websites. We extend previous research by evaluating the underlying structure of social media website usage motivations using a 13 item survey and evaluations from 19 different social media websites administered to 1686 young Americans. Using a multidimensional scaling approach, we uncover 2 major motive dimensions underlying social media website use: fun-related and content-specific. Based on the derived dimensions, we generate a graphical “quadrant” system for classifying social media websites and depict all 19 social media sites based on their quadrant. We propose that our quadrant system can be used by other researchers to further refine understanding of social media website usage motives.     

Already up? using mobile phones to track & share sleep behavior

Users share a lot of personal information with friends, family members, and colleagues via social networks. Surprisingly, some users choose to share their sleeping patterns, perhaps both for awareness as well as a sense of connection to others. Indeed, sharing basic sleep data, whether a person has gone to bed or waking up, informs others about not just one's sleeping routines but also indicates physical state, and reflects a sense of wellness. We present Somnometer, a social alarm clock for mobile phones that helps users to capture and share their sleep patterns. While the sleep rating is obtained from explicit user input, the sleep duration is estimated based on monitoring a user's interactions with the app. Observing that many individuals currently utilize their mobile phone as an alarm clock revealed behavioral patterns that we were able to leverage when designing the app. We assess whether it is possible to reliably monitor one's sleep duration using such apps. We further investigate whether providing users with the ability to track their sleep behavior over a long time period can empower them to engage in healthier sleep habits. We hypothesize that sharing sleep information with social networks impacts awareness and connectedness among friends. The result from a controlled study reveals that it is feasible to monitor a user's sleep duration based just on her interactions with an alarm clock app on the mobile phone. The results from both an in-the-wild study and a controlled experiment suggest that providing a way for users to track their sleep behaviors increased user awareness of sleep patterns and induced healthier habits. However, we also found that, given the current broadcast nature of existing social networks, users were concerned with sharing their sleep patterns indiscriminately.     

Finding interesting patterns using user expectations

One of the major problems in the field of knowledge discovery (or data mining) is the interestingness problem. Past research and applications have found that, in practice, it is all too easy to discover a huge number of patterns in a database. Most of these patterns are actually useless or uninteresting to the user. But due to the huge number of patterns, it is difficult for the user to comprehend them and to identify those interesting to him/her. To prevent the user from being overwhelmed by the large number of patterns, techniques are needed to rank them according to their interestingness. In this paper, we propose such a technique, called the user-expectation method. In this technique, the user is first asked to provide his/her expected patterns according to his/her past knowledge or intuitive feelings. Given these expectations, the system uses a fuzzy matching technique to match the discovered patterns against the user's expectations, and then rank the discovered patterns according to the matching results. A variety of rankings can be performed for different purposes, such as to confirm the user's knowledge and to identify unexpected patterns, which are by definition interesting. The proposed technique is general and interactive     

社交网络用户在在线媒体中点播行为预测

在线媒体快速发展,为用户带来丰富多彩信息的同时,用户的参与也给在线媒体本身带来巨大的经济利益。因此,如何通过精确预测用户的偏好以增加在线媒体点击,成为一个学术界和工业界均关注的问题。现有的预测方法主要是借助用户个人信息和历史行为来预测用户行为,然而此类方法没有考虑媒体本身缺乏用户信息造成无法预测的问题。随着社交网络的发展,在线媒体与服务运营商间的兼并或合作的增多,支持用户通过单一账户使用多个媒体网络服务的情况越来越常见,这就为基于用户在社交网络中的资料预测用户在其他媒体中的喜好提供海量可信的基础数据。该文基于社交网络Google+和视频媒体YouTube的数据,首先证明用户在YouTube偏好具有高度的集聚性,并提出用户在社交网络中偏好与其在线媒体点击行为具有关联性,基于这种关联性,该文使用社交网络用户信息预测用户在在线媒体中的点播行为。实验结果显示,使用社交网络用户信息可以有效预测用户偏好,预测准确率比仅使用媒体本身信息提高了17%,而且能满足用户个性化需求。