Topic-shift in Network Media Reports

It, from the perspective of cohesion, extracts three types of topic-shift markers used in this genre, namely 'change of narrators', 'change of objects being talked about', and 'temporal adverbials' to analyze four journalistic reports from the network media and draws the conclusion that cohesion between two topic units is usually weaker than that within a specific topic fragment.

Hybrid ants-like search algorithms for P2P media streaming distribution in ad hoc networks

Media streaming delivery in wireless ad hoc networks is challenging due to the stringent resource restrictions,po-tential high loss rate and the decentralized architecture. To support long and high-quality streams,one viable approach is that a media stream is partitioned into segments,and then the segments are replicated in a network and served in a peer-to-peer(P2P) fashion. However,the searching strategy for segments is one key problem with the approach. This paper proposes a hybrid ants-like search algorithm(HASA) for P2P media streaming distribution in ad hoc networks. It takes the advantages of random walks and ants-like algorithms for searching in unstructured P2P networks,such as low transmitting latency,less jitter times,and low unnecessary traffic. We quantify the performance of our scheme in terms of response time,jitter times,and network messages for media streaming distribution. Simulation results showed that it can effectively improve the search efficiency for P2P media streaming distribution in ad hoc networks.

Complex Network Formation and Analysis of Online Social Media Systems

To discover and identify the influential nodes in any complex network has been an important issue.It is a significant factor in order to control over the network.Through control on a network,any information can be spread and stopped in a short span of time.Both targets can be achieved,since network of information can be extended and as well destroyed.So,information spread and community formation have become one of the most crucial issues in the world of SNA(Social Network Analysis).In this work,the complex network of twitter social network has been formalized and results are analyzed.For this purpose,different network metrics have been utilized.Visualization of the network is provided in its original form and then filter out(different percentages)from the network to eliminate the less impacting nodes and edges for better analysis.This network is analyzed according to different centrality measures,like edge-betweenness,betweenness centrality,closeness centrality and eigenvector centrality.Influential nodes are detected and their impact is observed on the network.The communities are analyzed in terms of network coverage considering theMinimum Spanning Tree,shortest path distribution and network diameter.It is found that these are the very effective ways to find influential and central nodes from such big social networks like Facebook,Instagram,Twitter,LinkedIn,etc.

Determination of a Pore Structure Parameter of Porous Media by Analysis of Percolation Network Model

According to the simulation of nitrogen sorption process in porous media with three-dimensional network model, and the analysis for such a process with percolation theory, a new method is proposed to determine a pore structure parameter--mean coordination number of pore network, which represents the connectivity among a great number of pores. Here the 'chamber-throat' model and the Weibull distribution are used to describe the pore geometry and the pore size distribution respectively. This method is based on the scaling law of percolation theory after both effects of sorption thermodynamics and pore size on the sorption hysteresis loops are considered. The results show that it is an effective procedure to calculate the mean coordination number for micro- and meso-porous media.

AN ADAPTIVE OPPORTUNISTIC RETRANSMISSION CONTROL SCHEME ENVIRONMENT-AWARE-BASED FOR WIRELESS MULTIMEDIA MESH NETWORKS

In this paper, we propose an aware-based adaptive opportunistic retransmission control scheme for wireless multimedia Mesh networks. The proposed scheme provides maximum retransmis-sion count optimization based on environment-aware to improve packet relay probability. The scheme discriminates the types of packet loss in wireless link by means of environment information and selects the retransmission count by taking the IEEE 802.11 wireless channel characteristics into consideration. Furthermore, the maximum retransmission count of MAC is adjusted adaptively. Extensive simulations demonstrate that the proposed scheme significantly reduces packet collision probability and packet loss rate, and thus improves network throughput.

BulkTree: an overlay network architecture for live media streaming

Peer-to-peer (P2P) systems are now very popular. Current P2P systems are broadly of two kinds, structured and unstructured. The tree structured P2P systems used technologies such as distributed hash tables (DHT) and hierarchical clustering can search the required target quickly, however, in a tree, the internal node has a higher load and its leave or crash often causes a large population of its offspring's problems, so that in the highly dynamic Internet environment the tree structure may still suffer frequent breaks. On the other hand, most widely used unstructured P2P networks rely on central directory servers or massive message flooding, clearly not scalable. So, we consider both of the above systems' advantages and disadvantages and realize that in the P2P systems one node may fail easily, but that when a number of nodes organized as a set, which we call "super node", the set is robust. Super nodes can be created and updated aware of topology-aware, and used with simple protocol such as flooding or "servers" to exchange information. Furthermore the entire robust super node can be organized into exquisite tree structure. By using this overlay network architecture, P2P systems are robust, efficient, scalable and secure. The simulation results demonstrated that our architecture greatly reduces the alteration time of the structure while decreasing the average delay time, compared to the common tree structure.

Security Threat and Data Consumption as Mojor Nuisance of Social Media on Wi-Fi Network

This research is about the nuisances of social media applications on a Wi-Fi network at a university campus in Ghana. The aim was to access the security risk on the network, the speed of the network, and the data consumption of those platforms on the network. Network Mapper (Nmap Zenmap) Graphical User Interface 7.80 application was used to scan the various social media platforms to identify the protocols, ports, services, etc. to enable in accessing the vulnerability of the network. Data consumption of users’ mobile devices was collected and analyzed. Device Accounting (DA) based on the various social media applications was used. The results of the analysis revealed that the network is prone to attacks due to the nature of the protocols, ports, and services on social media applications. The numerous users with average monthly data consumption per user of 4 gigabytes, 300 megabytes on social media alone are a clear indication of high traffic as well as the cost of maintaining the network. A URL filtering of the social media websites was proposed on Rockus Outdoor AP to help curb the nuisance.

PARAMETERS INVERSION OF FLUID-SATURATED POROUS MEDIA BASED ON NEURAL NETWORKS

The multi- layers feedforward neural network is used for inversion ofmaterial constants of fluid-saturated porous media. The direct analysis of fluid-saturated porousmedia is carried out with the boundary element method. The dynamic displacement responses obtainedfrom direct analysis for prescribed material parameters constitute the sample sets training neuralnetwork. By virtue of the effective L-M training algorithm and the Tikhonov regularization method aswell as the GCV method for an appropriate selection of regu-larization parameter, the inversemapping from dynamic displacement responses to material constants is performed. Numerical examplesdemonstrate the validity of the neural network method.

移动边缘网络中基于QoE的网络媒体流卸载算法

针对移动边缘计算中新兴网络媒体流业务面临的高时延、高能耗、高带宽、低用户体验质量(QoE)等问题,提出一种基于QoE反馈配置卸载(QFCO)算法。首先,联合考虑预处理和优先级划分,从而最大化网络资源利用率,并为计算任务赋予不同的权重建立资源分配关系;然后,综合考虑截止时间、计算资源、功率和带宽等约束,以任务时延、能耗和精确度加权和为优化目标建立QoE模型,利用拉格朗日乘数法求解。仿真结果表明,相比深度增强学习在线卸载(DROO)算法,所提算法可有效实现资源的整体优化配置,更好地提升用户体验质量。

网络媒体国际中文教师身份的叙事定位构建

从叙事定位的视角出发,以网络媒体中有关国际中文教师的报道为例,运用叙事定位分析方法,构建新闻叙事框架。通过各种话语资源的分析,在不同层级的定位中展现国际中文教师身份的构建轨迹。研究发现,网络媒体中国际中文教师身份构建主要包括自身身份认同和责任身份认同。通过叙事定位“声音”及评价的过程,将国际中文教师定位为语言教育者、中华文化传播者和国际胸怀者等身份。国际中文教师身份的构建原因包括个人因素和社会因素,两者共同作用于其多元身份的构建过程。

GatherTweet: A Python Package for Collecting Social Media Data on Online Events

Social media plays a crucial role in the organization of massive social movements. However, the sheer quantity of data generated by the events as well as the data collection restrictions that researchers encounter, leads to a series of challenges for researchers who want to analyze dynamic public discourse and opinion in response to and in the creation of world events. In this paper we present gatherTweet, a Python package that helps researchers efficiently collect social media data for events that are composed of many decentralized actions (across both space and time). The package is useful for studies that require analysis of the organizational or baseline messaging before an action, the action itself, and the effects of the action on subsequent public discourse. By capturing these aspects of world events gatherTweet enables the study of events and actions like protests, natural disasters, and elections.

网络新媒体视阈下客家议题在日传播特征分析——基于日本Google News的考察

以日本Google News中的客家相关日文报道为语料,通过文本挖掘工具KH Coder进行文本数据挖掘,发现日本网络新闻媒体的客家议题日文报道具有分布零散性及以图片报道为主的特点。报道关注的客家区域主要涉及台湾地区、福建、香港地区、广东等地,其中,台湾地区的客家关注度最高。报道聚焦客家的观光旅游、产业振兴、客家书籍出版等相关内容,形成了客家传统建筑类、台湾地区客家文化交流类、客家文学作品推介类、客家观光旅游类等四大主要议题。本文提出要充分运用Google News等网络新媒体强大的技术功能和传播优势加大客家文化的传播力度。

网络主播失范行为及伦理引导

随着4G网络的普及,网络直播日益成为人们表达情感、满足需要、开展娱乐的重要手段。在政府、媒体、大众普遍看好网络直播行业发展前景的同时,各种违规、违法、失范、失德现象也日益突出,有的甚至已经构成严重犯罪。国家虽然颁布了一系列法律法规,但是网络失范行为仍旧时有发生。常见的网络失范行为有五种形式,包括网络欺诈、网络色情、网络恶搞、网络暴力、网络侵权,它们不但污染了网络生态环境,而且有悖社会主义核心价值观及公序良俗。导致网络主播持续失范的原因很多,从“现代性的隐忧”来看,主要包括市场机制被滥用,道德情感被割裂,社会责任被破坏,职业精神被亵渎四个方面。对于一般性失范行为而言,加强道德教育与伦理引导至关重要,其可以弥补“他律”的不足,提高“自律”的效能以及降低执法的成本。从康德的“定言命令”入手,通过弘扬当代美德伦理、重构常识道德体系、践行网络社交礼仪、谨防非正常快乐观,构建传统与现代,线上与线下相统一的伦理规范,是缓解“大脱嵌”带来的痛苦,实现个人自由以及网络生态和谐的必由之路。

新媒体背景下社会工作网络服务传播效果提升研究——基于短视频的数据分析

自2017年短视频成为新媒体的主要阵地之一后,短视频平台及其传播现象便逐渐成为一种宣传形象和文化传播的独特样态,给社会工作的发展带来了新的途径。为了更有效地利用短视频的优势,提升社会工作网络传播效果,通过在抖音、快手、小红书、哔哩哔哩以及微信视频号等平台收集社会工作主题短视频,利用SPSS26.0对视频主题、发布平台、发布方式、视频点赞量、收藏量、转发量、评论量等方面进行分析,并结合半结构式访谈了解现阶段社会工作者对社会工作短视频发展的态度,发现社会工作短视频的传播效果目前主要受视频主题、发布方式、发布平台三方面因素的影响,同时,视频剪辑技术、案主隐私、视频流量也限制了社会工作者制作和发布社会工作短视频。因此,应注重视频内容设计,打造品牌,引进和培养专业技术人才,加强社会工作的职业科普,积极探索平台引流方式,以保证社会工作网络传播的影响力。

新媒体时代高校辅导员加强网络育人的路径

依托先进的媒体技术开展网络育人是思政育人工作的必然趋势。将传统育人工作和新媒体技术融合,打造具有新媒体特色的育人模式,能够显著提升思政育人工作效率,全面提升学生的思想政治素养和道德水平。面对新媒体时代思政育人工作带来的挑战及机遇,高校应从开发网络育人平台、深入挖掘和利用育人资源,提升辅导员媒介修养及创新能力、构建专业化网络育人团队,构建健全的网络育人机制、牢固掌握网络意识形态工作主导权三方面入手,提高思政育人工作的吸引力、时代感和实效性,培育出满足时代发展需求的高素质人才,践行高校立德树人的根本任务。

发展“四全媒体”助力北京“四个中心”建设:问题与关键技术

新型媒体建设应该成为北京“四个中心”城市战略定位的重要助力。本文首先分析了“四个中心”建设对媒体的要求和发展“四全媒体”目前存在的技术和机制问题,然后通过示例探讨了发展“四全媒体”的技术可行性。实验结果表明“全程媒体”可以基于ICN网络的技术架构,基于写作风格的虚假信息识别技术和多语言新闻监测可以作为实现“全息媒体”的重要手段,“全效媒体”的媒体资产共享问题的解决可以基于区块链技术,分析表明分形理论、博弈论可能会成为“全员媒体”组织方式和机制制定的理论基础,最后提出了北京应自觉发展“四全媒体”的建议。