Explicating multitasking with computers: Gratifications and situations

This study tries to test the theory of uses and gratifications and the theory of situated action as explanations of multitasking in computer-mediated communication. Based on the data collected from an online survey (N = 234), we find that as hypothesized, different gratifications and situations are connected to different types of multitasking in different ways. In particular, multimedia and work-related multitasking are primarily driven by instrumental gratifications whereas affective gratifications contribute to multimedia and interaction type of multitasking. Situational factors have less powerful influence compared to gratifications. However, there are clear differences that discern types of computer multitasking along the situational dimension.     

大学生上网行为管理研究及对策

网络给大学生学习和生活提供了便捷的交流平台,但它是一把"双刃剑",也导致很多学生痴迷于网络.网络中的不良信息除对社会造成影响外,也对学生的生理、心理、行为等方面产生影响.本文通过对大学生上网行为问题研究,提出解决大学生上网行为问题的软硬策略,使上网行为管理得以完善.     

Exploring the Individual's Behavior on Self-Disclosure Online

Even though the ubiquity of technology can make many aspects of life more convenient, it may simultaneously raise some concerns about the privacy issues related to personal information. This research focused on the individual's behavior toward self-disclosure online and his or her cognition on personal privacy that was affected by not only the personal psychological factors but also the individual's computer knowledge and associated skills. To study how technological and psychological factors can simultaneously affect one's privacy concern and restrain behavior on disclosure, this study applied both perceived privacy and privacy concern to assess such factors as personal subjective attitude, computer self-efficacy, and perceived behavioral control to investigate the technological influence. A hypothesized model was proposed to describe the relationships among these constructs. After structural equation modeling is utilized to analyze the proposed hypotheses, the research findings showed that, although the perceived behavioral control had a negative effect on self-disclosure online, all the other hypotheses indicated a positive casual effect.     

一种基于判别随机场模型的联机行为识别方法

提出了一种基于判别随机场模型的联机行为识别方法,将传统的随机场模型和隐藏条件随机场模型的特点相结合,构建一个针对于运动序列帧数据建模的帧-隐藏条件随机场模型,并将该模型应用于数据驱动的行为建模,利用传统条件随机场模型对行为间的运动特性进行建模;通过引入隐藏特征函数,设计有效的特征模板来表示行为中子姿态的联系,实现对行为的内在运动特性进行建模.通过对比实验表明,该模型对于联机处理行为序列具有更强的识别能力.     

语义增强的在线学习行为预测研究

当前学习者的在线学习行为预测研究未充分利用短文本中的语义数据,导致对学习者的学习状态刻画不够全面,严重影响了行为预测的准确性.针对此问题,本文提出了语义增强的在线学习行为预测方法.首先,利用双向长短时记忆网络得到到短文本的语义向量表示;其次,基于学习者的统计、行为和短文本数据得到学习者的特征表征,并利用长短时记忆网络模型构建其学习状态表征;最后,利用学习状态表征预测学习者的学习行为.在11门真实在线课程数据集上的实验表明,本文方法能过有效提升在线学习行为预测的精确度.     

Sharing of Sponsored Advertisements on Social Media: A Uses and Gratifications Perspective

Organisations are increasingly utilising social media to advertise to, and interact with, consumers. Sponsored advertisements embedded into targeted users’ social media feeds appear less invasive than standalone advertisements but, unlike organic postings, incur financial cost. Given that friends’ posts attract most attention, this research employs Uses and Gratifications theory to determine salient motivations for users’ intentions to share sponsored advertisements, framed in the tourism context. Survey data was collected (n?=?487) and analysis revealed altruism, entertainment, socialising, and information seeking to be significant positive drivers of intention to share tourism-related sponsored advertisements on Facebook. Notably, information sharing was found to have a negative effect, while self-expression had no significant effect. In addition, the motivations were not found to significantly differ between males and females. This study contributes to theoretical understanding of users’ intentions to share sponsored advertisements within the social media environment and provides practical recommendations to help tourism marketers maximise reach.     

中国在线语言教育行业及用户行为分析

通过具体数据分析了在线语言教育行业的市场规模和增长率、用户总数、用户规模、用户区域分布情况等多个方面,总结了在线语言教育行业未来的趋势,为行业的发展提供数据支持.     

谈企业应该如何做员工上网行为管理

该文主要讨论了在企业中,如何从技术上实现对员工上网行为的有效管理,加强网络安全,降低运营成本。     

社交网络水军用户的动态行为分析及在线检测

利用社交网络用户的静态行为特征识别水军用户,无法检测水军用户的动态行为且难以应用于在线检测的环境。为此,构造社交网络用户的动态行为特征,分析正常用户和水军用户间的差异,以半监督模型为基础,结合动静行为特征构建在线检测模型,通过静态行为特征聚类及动态行为特征过滤筛选,使半监督模型利用最有价值的未标记用户数据进行增量学习,从而检测水军用户。实验结果表明,该模型的F1值高达93.33%,平均训练时间约为2 min,能够有效检测社交网络上的水军用户。     

基于在线学习行为分析的个性化学习推荐

随着在线课程和线上学习的普及,大量的在线学习行为数据被积累。如何利用数据挖掘技术分析积累的大数据,从而为教学决策和学习优化提供服务,已经成为新的研究重点。文中分析了在线学习的行为特征,挖掘学习者的性格特征与学习效率的关系,实现个性化学习方法推荐。首先,提取在线学习行为特征,并提出了一种基于BP神经网络的学习成绩预测方法,通过分析在线学习行为特征,预测其相应的线下学习成绩;其次,为了进一步分析学习者的在线学习行为与成绩的关系,提出了基于实际熵的在线学习行为规律性分析,通过分析学习者的在线学习行为,定义并计算相应的实际熵值来评估个体的学习行为规律性,从而分析规律性与最终成绩的关系;再次,基于Felder-Silverman性格分类法获得学习者的性格特征,对学习者实现基于K-means的聚类分析获得相似学习者的类别,将学习成绩较优的学习者的在线学习习惯推荐给同一类别的其他学习者,从而提高学习者的在线学习效率;最终,以某在线课程平台的实际数据为实验对象,分别实现在线学习行为特征提取、线下成绩预测、学习规律性分析和个性化学习推荐,从而验证了所提方法的有效性和应用价值。     

一种干部在线作弊学习行为分析与预测策略

干部学习已通过互联网实现信息化与数字化,但部分干部采取作弊手段来完成学习要求。为提高干部学习质量与效益,针对利用插件等工具进行作弊学习的现象,根据防作弊规则,提出一种干部在线作弊学习的检测策略。通过分析学习数据发现作弊行为,并对作弊行为进行预测。应用结果表明,该策略能够有效提升在线学习质量,对学习效果做到准确评价,有利于促进干部在线教育的健康发展。     

基于网络学习行为的学习者本体构建

随着多媒体技术的发展,教育技术进入到大数据时代,数据挖掘等学习技术对教育领域的各种原理研究十分重要,然而怎样把数据挖掘这种技术有效的应用到教育教学中是问题的关键所在。其中,本体构建就是一个重要的方法,该方法将会对研究行为规律、分析学生的行为产生重大的影响。本文在已有本体构建方法基础上,通过总结本体构建过程,设计网络学习空间中学习者本体构建方法并成功实施,最后对学习者本体进行一致性分析。这将为学习者提供精准的教学支持服务,实现个性化学习。同时,学习者本体的成功构建也将为智慧教育提供重要帮助。     

面向在线交易日志的用户购买行为可视化分析

在线交易日志,即用户通过电商平台购买商品产生的交易记录,包括用户、商品、交易及商家的相关信息,反映了用户的购买行为.现有的可视化方法未能充分结合在线交易日志的时序、层次、地理、多维等特征,实现对用户购买行为的多角度分析.对此,本文结合交易日志的多个特征,提出了基于径向布局的复合时序可视化方法和融合空间信息的时间轴可视化方法,设计了颜色极值映射方法和规律映射方法,并基于上述方法,设计并实现了面向在线交易日志的用户购买行为可视化分析系统UPB-VIS,从而完成了单个用户和用户群体购买行为的全方位分析.最后,通过在京东商城在线交易日志数据集上的实验证明了系统的易用性和相关可视化方法的有效性.     

基于数据挖掘技术的在线学习行为研究综述

随着互联网 教育技术的快速发展,慕课已成为当下最新、最潮的学习形式。由于在线学习平台积累了大量学习行为数据,传统统计分析方法已无法满足应用需求,使得数据挖掘技术被引入在线学习行为的研究,从而涌现出大量的研究成果。为了深入分析在线学习行为研究中数据挖掘技术的整体应用情况,本文首先从国内外公认的Web of Science数据库收集2008年至2017年3月相关文献进行了统计和可视化分析;然后介绍了利用数据挖掘技术进行在线学习行为研究的一般流程;接着将数据挖掘技术在在线学习行为研究中的应用总结归纳为五类,并详细介绍了相关研究成果及代表文献;最后总结全文,并讨论了未来可能的研究方向。     

Online Affect Detection and Robot Behavior Adaptation for Intervention of Children With Autism

Investigation into robot-assisted intervention for children with autism spectrum disorder (ASD) has gained momentum in recent years. Therapists involved in interventions must overcome the communication impairments generally exhibited by children with ASD by adeptly inferring the affective cues of the children to adjust the intervention accordingly. Similarly, a robot must also be able to understand the affective needs of these children—an ability that the current robot-assisted ASD intervention systems lack—to achieve effective interaction that addresses the role of affective states in human–robot interaction and intervention practice. In this paper, we present a physiology-based affect-inference mechanism for robot-assisted intervention where the robot can detect the affective states of a child with ASD as discerned by a therapist and adapt its behaviors accordingly. This paper is the first step toward developing “understanding” robots for use in future ASD intervention. Experimental results with six children with ASD from a proof-of-concept experiment (i.e., a robot-based basketball game) are presented. The robot learned the individual liking level of each child with regard to the game configuration and selected appropriate behaviors to present the task at his/her preferred liking level. Results show that the robot automatically predicted individual liking level in real time with 81.1% accuracy. This is the first time, to our knowledge, that the affective states of children with ASD have been detected via a physiology-based affect recognition technique in real time. This is also the first time that the impact of affect-sensitive closed-loop interaction between a robot and a child with ASD has been demonstrated experimentally.      

Gratifications and social network service usage: The mediating role of online experience

This paper incorporates dual theories from communication research (uses and gratifications) and psychology research (online flow) to examine consumer behavior in the use of social network services. In particular, the study proposes that consumers’ online experience of interaction and arousal serves as the mediator of the relationship between social motivations and use behaviors. The empirical results indicate that arousal fully mediates the relationship between social gratifications and problematic social network service use. Furthermore, both interaction and arousal are partial mediators of the relationship between social gratifications and the intention to revisit social networking websites.     

Effect of Network Quality on Player Departure Behavior in Online Games

Understanding the impact of network conditions on player satisfaction, which is one of the major concerns of network game designers, is a popular research topic. Of the various ways to gauge user satisfaction, in this paper, we focus on how network quality affects a player's decision to leave a game prematurely. To answer this question, we analyze a 1,356-million-packet trace from a large commercial massively multiplayer online role-playing game (MMORPG) called ShenZhou Online. We show that both network delay and network loss significantly affect a player's decision to leave a game prematurely. It is feasible to predict whether players will quit prematurely based on the network conditions they experience. The proposed model can determine the relative impact of different types of network impairment. For our traces, the degrees of player intolerance to network delay, delay jitter, client packet loss, and server packet loss are in the proportion of 1:2:4:3 approximately. The model can also be used to make system design decisions. Through simulations, we show that by prioritizing server processing according to the goodness of network conditions, employing dejitter buffers, or replacing TCP with a more lightweight transport protocol, the probability of premature departure can be significantly reduced. In this way, we demonstrate how our model of players' network experience provides feedback for the design of online games.     

Mobile Instant Messengers and Middle-Aged and Elderly Adults in Taiwan: Uses and Gratifications

For middle-aged and elderly adults with potential capabilities in finance, eagerness to keep up with the times using a mobile instant messenger (MIM) is an indispensable quality. Mobile social networking services take a wide range of forms, among which an MIM, which logs in when one opens an app (application), is a representative “core service” of the information technology (IT) system. LINE is a good example of an MIM and is particularly popular in Taiwan. This article aims to understand, through the study of other social messengers, middle-aged and elderly adults’ uses of and gratifications related to for the LINE system; this study also aims to provide opinions and suggestions related to future app design, development, and research. The results show that middle-aged and elderly adults use MIM to maintain their social activities and relationships for purposes related to affection, information, stress relief, popularity, concern, and applications. We further confirm that if middle-aged and elderly adults use a larger number of LINE features, they will use them for longer time per day and more frequently per week, and they will receive more gratification from their “behavior of use.”     

网络游戏案例研究: 用户行为分析和流失预测过

用户流失预测在很多领域得到关注,目前主流的用户流失预测方法是使用分类法。网络游戏领域发展迅猛,但用户特征选取、特征处理和流失预测的相关研究较少。本文以一款网页网络游戏的用户记录为数据,对用户游戏行为进行分析对比,发现流失用户在游戏投入、博彩热情、玩家互动方面与正常用户存在显著差异;同时发现网络游戏数据存在样本分布不平衡、候选特征库庞大和干扰差异多等难点。在此分析基础上,本文探讨了网游用户的关键特征提取的关注方向,以及归一化和对齐化在特征处理中的关键作用。实验表明,本文提取的特征具有很好的区分度。     

在线旅游社区用户行为规律的探讨

本文通过抽样采集国内最大的在线旅游社区平台马蜂窝中的用户成员帖子数据,进行预处理并借助数据挖掘技术进行挖掘,从而获得在线旅游社区的用户潜在的行为规律,并对这些行为规律进行相关描述.基于关联规则数据挖掘的在线旅游社区用户行为规律研究结果具有一定的意义,可为在线旅游社区的运营者开展针对性的运营提供有益的参考.