共查询到20条相似文献，搜索用时 15 毫秒
1.
Nicola Green 《The Information Society》2002,18(4):281-292
The current explosion in mobile computing and telecommunications technologies holds the potential to transform "everyday" time and space, as well as changes to the rhythms of social institutions. Sociologists are only just beginning to explore what the notion of "mobility" might mean when mediated through computing and communications technologies, and so far, the sociological treatment has been largely theoretical. This article seeks instead to explore how a number of dimensions of time and space are being newly reconstructed through the use of mobile communications technologies in everyday life. The article draws on long-term ethnographic research entitled "The Socio-Technical Shaping of Mobile Multimedia Personal Communications," conducted at the University of Surrey. This research has involved ethnographic fieldwork conducted in a variety of locales and with a number of groups. This research is used here as a resource to explore how mobile communications technologies mediate time in relation to mobile spaces. First the paper offers a review and critique of some of the major sociological approaches to understanding time and space. This review entails a discussion of how social practices and institutions are maintained and/or transformed via mobile technologies. Ethnographic data is used to explore emerging mobile temporalities. Three interconnected domains in mobile time are proposed: rhythms of mobile use, rhythms of mobile use in everyday life, and rhythms of mobility and institutional change. The article argues that while these mobile temporalities are emerging, and offer new ways of acting in and perceiving time and space, the practical construction of mobile time in everyday life remains firmly connected to well-established time-based social practices, whether these be institutional (such as clock time, "work time") or subjective (such as "family time"). 相似文献
2.
3.
《Information processing & management》2020,57(3):102087
With the rapid development in mobile computing and Web technologies, online hate speech has been increasingly spread in social network platforms since it's easy to post any opinions. Previous studies confirm that exposure to online hate speech has serious offline consequences to historically deprived communities. Thus, research on automated hate speech detection has attracted much attention. However, the role of social networks in identifying hate-related vulnerable community is not well investigated. Hate speech can affect all population groups, but some are more vulnerable to its impact than others. For example, for ethnic groups whose languages have few computational resources, it is a challenge to automatically collect and process online texts, not to mention automatic hate speech detection on social media. In this paper, we propose a hate speech detection approach to identify hatred against vulnerable minority groups on social media. Firstly, in Spark distributed processing framework, posts are automatically collected and pre-processed, and features are extracted using word n-grams and word embedding techniques such as Word2Vec. Secondly, deep learning algorithms for classification such as Gated Recurrent Unit (GRU), a variety of Recurrent Neural Networks (RNNs), are used for hate speech detection. Finally, hate words are clustered with methods such as Word2Vec to predict the potential target ethnic group for hatred. In our experiments, we use Amharic language in Ethiopia as an example. Since there was no publicly available dataset for Amharic texts, we crawled Facebook pages to prepare the corpus. Since data annotation could be biased by culture, we recruit annotators from different cultural backgrounds and achieved better inter-annotator agreement. In our experimental results, feature extraction using word embedding techniques such as Word2Vec performs better in both classical and deep learning-based classification algorithms for hate speech detection, among which GRU achieves the best result. Our proposed approach can successfully identify the Tigre ethnic group as the highly vulnerable community in terms of hatred compared with Amhara and Oromo. As a result, hatred vulnerable group identification is vital to protect them by applying automatic hate speech detection model to remove contents that aggravate psychological harm and physical conflicts. This can also encourage the way towards the development of policies, strategies, and tools to empower and protect vulnerable communities. 相似文献
4.
Pille Pruulmann-Vengerfeldt 《The Information Society》2006,22(5):303-310
Using Layder's domain theory (1997) as an analytical framework, this article shows how the information society can be measured through various levels of society. Layder's notions of psychobiography, situated activity, social setting, and contextual resources help identify cultural and social indicators for understanding changes in the information society. With the help of empirical indicators for each domain, this article uses the case of Estonia to show that there is often more to the information society than what is captured by traditional measures. This article calls for a context-sensitive approach, which takes into consideration social and cultural indicators. Measurements from all four domains are necessary for understanding the complexity of information-society-related issues. 相似文献
5.
This paper examines nongoal oriented transactions with texts in order to investigate the information encounter in the context of daily living. Findings are reported from a larger research project based on intensive interviews with 194 committed readers who read for pleasure. The paper analyses interview responses that illuminate two aspects of the readers' experience of reading for pleasure: (1) how readers choose books to read for pleasure; and (2) books that have made a significant difference in readers' lives. The paper concludes with five themes emerging from this analysis that have implications for the information search process: the active engagement of the reader/searcher in constructing meaning from texts; the role of the affective dimension; ‘trustworthiness’; the social context of information seeking; and the meta-knowledge used by experienced readers in making judgments about texts. 相似文献
6.
认为在当今科学和技术密切结合且同时作为由社会和国家组织起来的社会活动和社会建制深刻影响现代社会之时,科学技术除作为以经济、政治、文化、法律为语境的文本存在外,同时也作为政治、经济、文化、法律等这些文本的语境存在,赋予这些文本以意义,因而,其与作为现代社会重要制度性、程序性和技术性调控机制的法律之间这种互为文本和语境的关系,以及作为其表征的二者间相通与互异、互动与受制的复杂关系就当同时进入科学学和法学的研究视野。 相似文献
7.
构建了移动社交网络基于情景化用户偏好的自适应适配信息服务系统模型,提出了移动社交网络的自适应服务发现方案。解决移动社交网络信息服务的发现与推送的延迟问题,实现高效的移动社交网络信息服务推送,对移动社交网络信息服务资源、知识资源进行科学管理。 相似文献
8.
[目的/意义]针对移动社交媒体倦怠行为进行理论分析,有利于帮助企业或相关组织更好地持续利用社交媒体工具开展相关的业务及公共服务。[方法/过程]基于"感知-态度-行为"研究范式,结合计划行为理论、隐私计算理论以及心流理论内容,构建移动社交媒体倦怠行为的影响因素模型,并通过实证研究方法对模型的适用性进行检验。[结果/结论]数据分析结果表明,"自我效价"对移动社交媒体态度不存在显著关系;"隐私保护"和"信息过载"对移动社交媒体态度具有显著的负向影响作用;"心流体验"对移动社交媒体态度具有正向的影响作用;"社交媒体态度"对移动社交媒体倦怠具有显著的正向影响作用。 相似文献
9.
Potential for the use of mobile wallet is enormous and it is drawing attention as an alternative mode of payment worldwide. The present research aims to provide important insights into the TAM (Technology Acceptance Model) and UTAUT2 (Unified Theory of Acceptance and Use of Technology) models. This study develops a conceptual model to determine the most significant factors influencing user's intention, perceived satisfaction and recommendation to use mobile wallet. The research model included 206 responses from an online and manual survey in India. Our study tested the moderating effect of innovativeness, stress to use and social influence on user's perceived satisfaction and recommendation to use mobile wallet services. We found that ease of use, usefulness, perceived risk, attitude, to have significant effect on user's intention, which further influenced user's perceived satisfaction and recommendation to use mobile wallet services. We also determined the significant moderating effect of stress to use and social influence on user's perceived satisfaction and recommendation to mobile wallet services. This study provides an integrated framework for academicians to measure the moderating effect of psychological, social and risk factors on technology acceptance. It can also help practitioners by identifying important factors affecting user's decision, which further affects user's perceived satisfaction and recommendation to use mobile wallet services. 相似文献
10.
文章分析了科研信息化发展态势,认为当前科研信息化发展将进入第三阶段即"一体化"阶段,并将发展态势凝练为"五新":大数据驱动科研范式变革成为"新亮点",开放科学借力科研信息化成为"新趋势",科研移动应用成为科研创新的"新动力",科研信息化基础设施性能及规模加速发展和升级成为"新常态",科研信息化推动企业创新和产学研协同创新成为"新模式"。指出了我国在科研信息化基础设施与应用领域面临的挑战;介绍了中科院在科研信息化基础设施、科学大数据、科研信息化应用3个方面的发展部署;提出了针对我国科研信息化的发展建议,包括建立国家科研信息化发展体系,实施国家级科研信息化工程,建设面向全国科技界提供科技资源和信息化资源的综合服务平台等。 相似文献
11.
The use of the internet and social media have changed consumer behavior and the ways in which companies conduct their business. Social and digital marketing offers significant opportunities to organizations through lower costs, improved brand awareness and increased sales. However, significant challenges exist from negative electronic word-of-mouth as well as intrusive and irritating online brand presence. This article brings together the collective insight from several leading experts on issues relating to digital and social media marketing. The experts’ perspectives offer a detailed narrative on key aspects of this important topic as well as perspectives on more specific issues including artificial intelligence, augmented reality marketing, digital content management, mobile marketing and advertising, B2B marketing, electronic word of mouth and ethical issues therein. This research offers a significant and timely contribution to both researchers and practitioners in the form of challenges and opportunities where we highlight the limitations within the current research, outline the research gaps and develop the questions and propositions that can help advance knowledge within the domain of digital and social marketing. 相似文献
12.
《Information processing & management》2019,56(6):102060
In this era, the proliferating role of social media in our lives has popularized the posting of the short text. The short texts contain limited context with unique characteristics which makes them difficult to handle. Every day billions of short texts are produced in the form of tags, keywords, tweets, phone messages, messenger conversations social network posts, etc. The analysis of these short texts is imperative in the field of text mining and content analysis. The extraction of precise topics from large-scale short text documents is a critical and challenging task. The conventional approaches fail to obtain word co-occurrence patterns in topics due to the sparsity problem in short texts, such as text over the web, social media like Twitter, and news headlines. Therefore, in this paper, the sparsity problem is ameliorated by presenting a novel fuzzy topic modeling (FTM) approach for short text through fuzzy perspective. In this research, the local and global term frequencies are computed through a bag-of-words (BOW) model. To remove the negative impact of high dimensionality on the global term weighting, the principal component analysis is adopted; thereafter the fuzzy c-means algorithm is employed to retrieve the semantically relevant topics from the documents. The experiments are conducted over the three real-world short text datasets: the snippets dataset is in the category of small dataset whereas the other two datasets, Twitter and questions, are the bigger datasets. Experimental results show that the proposed approach discovered the topics more precisely and performed better as compared to other state-of-the-art baseline topic models such as GLTM, CSTM, LTM, LDA, Mix-gram, BTM, SATM, and DREx+LDA. The performance of FTM is also demonstrated in classification, clustering, topic coherence and execution time. FTM classification accuracy is 0.95, 0.94, 0.91, 0.89 and 0.87 on snippets dataset with 50, 75, 100, 125 and 200 number of topics. The classification accuracy of FTM on questions dataset is 0.73, 0.74, 0.70, 0.68 and 0.78 with 50, 75, 100, 125 and 200 number of topics. The classification accuracies of FTM on snippets and questions datasets are higher than state-of-the-art baseline topic models. 相似文献
13.
移动阅读用户满意度与持续使用意愿影响因素研究——以内容聚合类APP为例 总被引：1，自引：0，他引：1
近年来,移动阅读服务中用户的持续使用与黏性受到了学界和业界的关注。在分析移动阅读特点的基础上,基于ECM-IT模型和DM模型,构建了新的持续使用意愿研究模型,并通过实证研究,得到了以下结论:一是扩展后的ECM-IT和DM模型适用于移动阅读情境;二是满意度、感知有用性、感知娱乐性等因素对用户持续使用有显著影响;三是移动阅读服务的内容、界面、个性化服务等功能对用户满意度有显著影响,分享、转发、评论等社交化互动服务对用户满意度没有显著影响。 相似文献
14.
Is it possible to identify crime suspects by their mobile phone call records? Can the spatial-temporal movements of individuals linked to convicted criminals help to identify those who facilitate crime? Might we leverage the usage of mobile phones, such as incoming and outgoing call numbers, coordinates, call duration and frequency of calls, in a specific time window on either side of a crime to provide a focus for the location and period under investigation? Might the call data records of convicted criminals' social networks serve to distinguish criminals from non-criminals? To address these questions, we used heterogeneous call data records dataset by tapping into the power of social network analysis and the advancements in graph convolutional networks. In collaboration with the Punjab Police and Punjab Information Technology Board, these techniques were useful in identifying convicted individuals. The approaches employed are useful in identifying crime suspects and facilitators to support smart policing in the fight against the country's increasing crime rates. Last but not least, the applied methods are highly desirable to complement high-cost video-based smart city surveillance platforms in developing countries. 相似文献
15.
我们在上网浏览网页的时候,经常会遇到许多鼠标右键被禁止使用或者禁止复制该网页中内容等情况.在这些情况下,网页上面的文字、图片通过正常的方法都无法进行复制.但是网页上面的内容却是我们非常喜欢和需要的,不管是图片还是文字我们都想保存到本地磁盘上以便日后查看和使用,那我们应该如何解决这样的限制呢?笔者将根据自己多年的使用经验,在本文中将几种简单实用的方法作一下汇总,以供大家在今后使用. 相似文献
16.
我国行业协会理论发展研究综述 总被引：1，自引：0，他引：1
本文对近年来我国有关行业协会理论研究做一梳理性的概括,除了对行业协会的概念界定表示质疑外,也归纳分析了行业协会研究的理论视角、社会功能及其生成机制,并提出了可进一步展开研究的方向。 相似文献
17.
世界经济的飞速发展使得以创新推动制造业高质量发展迫在眉睫,为使制造业的创新达到最佳水平,我国政府先后发布多项政策激励其发展,已有政策设定是否合理、文本内容是否符合现实需求是今后发布相关政策的重要依据。本文利用社会网络分析和共词分析等方法深入分析2012-2019年间国家发布的78项制造业创新政策文本的内容,以此为基础构建制造业创新政策评价的量化框架,选取具有代表性的政策为样本,利用PMC-AE指数模型进行量化评价。结果表明：政策样本得分均较高,说明相关政策颁布机构制定的政策质量较高,政策文本内容的设定较为合理且符合现实需求,但仍存在一些问题亟需完善,包括增加政策文本中涉及监管及规范的内容、加强政策工具的组合运用、扩大政策参与对象的覆盖范围、完善激励保障措施的运用及加强政策颁布机构之间协同的广度与深度。 相似文献
18.
[目的/意义]对社交媒体中热门新闻的及时识别,有助于加速正面资讯的投送或抑制负面资讯的扩散。当前,基于自然语言处理的传统识别方法正面临社交媒体新生态的挑战：大量新闻内容以图片、音视频形式存在,缺乏用于语义及情感分析的文本。[方法/过程]对此,本文首先将社交网络划分为众多社群,并按其层次结构组织为贝叶斯网络。接着,面向社群构建基于卷积神经网络的热门新闻识别模型,模型综合考虑新闻传播的宏观统计规律及微观传播过程,以提取社群内热门新闻传播的特征。最后,利用贝叶斯推理并结合局部性的模型识别结果进行全局性热度预测。[结果/结论]实验表明,本方法在语义缺失场景下可有效识别热门新闻,其准确度强于基于语义信息的机器学习方法,模型具有良好的时效性、可扩展性和适用性。该研究有助于社交媒体的监管机构及时识别出各类不含语义信息且迅速扩散的热点内容。 相似文献
19.
【目的/意义】随着网络购物的普及,在线评论成为影响消费者、销售者和生产者决策的重要数据。大数据
时代,在线评论呈现出多源异构、爆发式增长的特点,难以为用户的购买决策和商家竞争提供有力的情报支撑。【方
法/过程】本文利用多源异构的在线评论数据构建知识图谱,提出了一种基于多源异构数据构建知识图谱的框架,
模式层构建围绕在线评论的信源、内容以及形式构建,最终形成知识图谱的概念框架,并运用word2vec从多源异构
文本中获取实体、关系和属性,并进行数据融合与知识图谱分析。【结果/结论】实验部分以手机商品在线评论为例,
验证了本文所构建的知识图谱对在线评论相关研究及挖掘的有效性,研究结果揭示了多源异构在线评论数据的特
点,为大数据环境下在线评论信息组织、展示和挖掘提供了新的研究视角。【创新/局限】运用知识图谱对在线评论
进行描述,有效解决信息过载、多源异构信息融合等问题。本文采用半自动化的方式构建知识图谱,未来考虑引入
无监督的方法提高构建效率。 相似文献
20.
比较社会科学和自然科学在研究对象、研究方法、科学基础与“认识旨趣”、理论特征、理论与实践的关系等5个方面的差异。认为研究对象上的差异处于核心地位。现代社会科学的科学性建立在社会分工的基础上。相对于自然科学而言,社会科学理论很少有“范式”和创造性,但它仍然对社会具有重要的建构作用。 相似文献