Identifying the combinations of motivations and emotions for creating satisfied users in SNSs: An fsQCA approach

Social Networking Sites (SNSs) play an important role in our daily lives and the number of their users increases regularly. To understand how users can be satisfied in the complex digital environment of SNSs, this study examines how motivations and emotions combine with each other to explain high satisfaction. Users’ motivations comprise four attributes, entertainment, information, social-psychological, and convenience. Emotions are divided into their two main categories, that is positive and negative emotions. We draw on complexity and configuration theories, present a conceptual model along with propositions and perform a fuzzy-set qualitative comparative analysis (fsQCA). Through an empirically study with 582 SNSs users, we present eight combinations (configurations) of motivations and emotions that lead to high satisfaction, which highlight the role of high convenience, followed by entertainment and information motivations in being satisfied with SNSs. High satisfaction can be achieved both when positive and negative emotions are high and low, depending on how they combine users’ motivations. None of the factors are indispensable to explain high satisfaction on their own, instead they are insufficient but necessary parts of the causal combinations that explain high satisfaction. This study contributes in SNSs literature by extending current knowledge on how motivations and emotions combine to increase satisfaction, and by identifying specific patterns of users for whom these factors are important and influence greatly their satisfaction.     

体育锻炼动机研究综述

动机是推动一个人进行活动的心理动因或内部动力。文章回顾了体育锻炼动机的的理论基础，介绍了体育锻炼动机的组成成分和常用的测量工具，从动机的年龄差异、性别差异、文化程度差异、经济收入差异、社会文化差异五个方面概括了以往相关研究的成果，并指出了目前研究中存在的问题。     

基于本体的语义检索技术研究与实现

在本体基础上通过语义相似度和相关度的计算,利用语义推理将描述的隐含语义显式化,以充分挖掘出与检索内容相关的信息,实现相关信息的语义融合,提高查准率和查全率。研究基于本体的语义相似度和相关度的计算方法,并通过该语义检索方法的实现,证明该方法在语义检索系统开发中的可行性。     

情报检索语言研究的新领域

情报检索语言的发展面临现代化、理论方法综合化和集成化的新条件,研究新的语言模型,提高检索语言的表达、描述等功能是当前的重要研究课题,同时要具体研究数据库检索语言、网络检索语言、本体论和语义网检索语言。在所有这些领域里,检索语言的机器理解功能日益重要;为适应机器处理的环境,对它的逻辑推理能力的要求越来越高,知识建模功能与系统表达能力受到越来越多的重视。     

中文信息处理中的语义关系表示探析

根据目前中文信息处理的现状对自然语言在句法结构与语义结合方面的需求，对美国加州大学伯克利分校构建的框架网络工程进行探索与研究，详细分析框架网络数据库中最重要的框架关系，并利用这些关系将词汇进行联系形成网状数据库，目的在于利用词与词间的关系进行信息抽取或信息检索时，能够方便准确地进行信息处理并得到理想结果。     

DC词表的维护:实践、策略与模型

DCMI维护着一个包含众多元数据术语的词表，其中最主要的是包括15个元素的都柏林核心。然而，DCMI所关注和讨论的并不只是这个核心集，以及围绕这个核心集的实践、策略和模型，DC元数据模型已经由最初的单一模型进化成一个完整的框架，可以通过这个框架对应用DC元数据的各种实践进行评估。这些术语及其以前的版本现在都由统一资源标识符(URI)来标识，并建立了网页和形式化的schema文档，在注册系统中被编成索引，在具体的应用纲要(application profiles)中被引用。DCMI正在寻求一种简单易行的维护机制，一方面推荐使用不断变化和增长的核心标准，另一方面承认和重用其它的词表作为必要的补充，这两者之间需要建立一种平衡。     

基于本体论的语义导航模型研究

本文通过对信息导航的现状分析，提出基于本体论的语义导航思想，研究了基于本体论的信息组织，构建了基于本体论的语义导航模型，并结合实例探讨了语义导航的实现原理。     

基于Ontology的语义导航研究*

提出基于Ontology建立导航机制，赋予导航语义，可以改善WWW导航的现状。本文主要讨论了Ontology及其对导航的支持，并给出一个基于Ontology的语义导航模型。     

基于数据库联邦方式的多数据源集成检索系统

介绍了多数据源集成检索系统的产生背景和实现方式，分析了基于数据库联邦方式的多数据源集成检索系统的体系框架和异构问题，对国外的基于数据库联邦方式的多数据源集成检索系统进行了介绍和比较分析。     

Confidence in prior knowledge,self-efficacy,interest and prior knowledge: Influences on conceptual change

This study explored how confidence in prior knowledge, self-efficacy, interest, and prior knowledge interact in conceptual change learning. One hundred and sixteen college students completed an assessment of confidence in prior knowledge, self-efficacy, interest, prior scientific understanding, and prior misconceptions before reading a refutation text on seasonal change. Students’ misconceptions and scientific understanding of seasonal change was then assessed before and after reading a refutation text, and again at a two week delayed posttest. Three profiles of students emerged based on their confidence in prior knowledge, self-efficacy, interest, prior scientific understanding, and prior misconceptions. The profiles included: (1) Low (low confidence, self-efficacy, interest, and prior scientific understanding and high prior misconceptions), (2) mixed (high confidence, self-efficacy, and interest, but low prior scientific understanding and high prior misconceptions), and (3) high (high confidence, self-efficacy, interest, and prior scientific understanding and low prior misconceptions). Results indicated that the mixed profile appeared to be most productive for conceptual change and that learner characteristics most productive for conceptual change learning may differ from those most productive in other learning situations.