Camtasia in the Classroom: Student Attitudes and Preferences for Video Commentary or Microsoft Word Comments During the Revision Process

In the last ten years, libraries, individual departments, and professors have experimented with screen-capture software to develop edited tutorials, record in-class lectures via presentation software, and record think-aloud rationale for difficult problem sets. Moreover, screen-capture software has been used to provide visual/audio feedback for student writing. Currently, there is scant research on visual/audio feedback via screen-capture software in writing courses. The present study examines student perceptions and attitudes about two different modes and media of teacher feedback: Microsoft Word comments versus visual/audio commentary. The results indicate that the mode and medium of teacher feedback had an impact on students’ perceptions about the rhetorical context of the revision process and perceptions about the teacher/student relationship. Students who preferred the visual/audio modality of the teacher commentary videos cited their conversational quality, clarification of expectations, and reference to more global issues in writing. On the other hand, students who preferred the Microsoft Word comments were more apt to discuss its indexical quality in that students could easily revise surface level features or locate the “problem” sentence. The results also indicate that an either/or approach to teacher feedback is not necessary. Students articulated the relevance of using a combination approach in which Microsoft Word comments and the teacher commentary videos could be used for different elements or stages of the writing process. As instructors transition to teaching within online contexts and experiment with new technologies, it is important to examine the significance of the mode and medium of teacher feedback in student perceptions, participation, and writing practices.     

基于异构图注意力网络的微博谣言监测模型

社交媒体方便了人们的日常交流和信息传播,同时也是谣言滋生和传播的温床,因此如何在谣言传播早期自动监测极具现实意义,而现有的检测方法没有充分利用微博信息传播图的语义信息。为了解决这个问题,基于异构图注意力网络（HAN）构建了谣言监测模型MicroBlog-HAN。该模型采用含有节点级注意力和语义级注意力的分层注意力机制。首先,节点级注意力结合微博节点的邻居生成两组具有特定语义的节点嵌入;然后,语义级注意力融合不同语义,得到最终的节点嵌入,并输入到分类器中执行二分类任务;最后,给出输入微博是谣言还是非谣言的分类结果。在两个真实的微博谣言数据集上的实验结果表明,MicroBlog-HAN模型可以实现微博谣言较准确的识别,准确率超过87%。     

微博信息传播预测研究综述

微博已经逐渐成为人们获取信息、分享信息的重要社会媒体,深刻影响并改变了信息的传播方式.针对微博信息传播预测问题展开综述.该研究对舆情监控、微博营销、个性化推荐具有重要意义.首先概述微博信息传播过程,通过介绍微博信息传播的定性研究工作,揭示微博信息传播的特点;接着,从以信息为中心、以用户为中心以及以信息和用户为中心这3个角度介绍微博信息传播预测相关研究工作,对应的主要研究任务分别是微博信息流行度预测、用户传播行为预测和微博信息传播路径预测;继而介绍可用于微博信息传播预测研究的公开数据资源;最后,展望微博信息传播预测研究的问题与挑战.     

微博客蕴含交通事件信息抽取的自动标注方法

微博客文本蕴含丰富的实时交通事件信息,能够为现有交通信息采集手段提供补充。然而,当前事件抽取方法缺少对地理实体关系的判断过程,对涉及多个地理实体及关系表达的地理空间要素抽取效果不佳,难以准确识别交通事件信息的位置描述。该文提出一种自动标注方法,将地理实体关系识别引入事件抽取过程来解决这一问题。该方法利用条件随机场模型实现交通事件角色标注,利用支撑向量机模型实现角色关系与要素关系标注,完成了交通事件信息空间要素识别。以新浪微博为数据源开展的实验分析表明,该文所提出的微博客蕴含交通事件抽取方法,正确率和召回率均达到90%,优于现有的基于模式匹配的抽取方法。     

基于种子词的微博表情符情感倾向判定方法

情感倾向明显的表情符,容易通过人工进行标注。但是对于情感倾向不明显的表情符,多人手工的标注结果往往难以达成一致。因此,提出一种利用种子词自动判定表情符情感倾向的方法。该方法利用少量种子表情符自动标注情感倾向比较明显的表情符,生成表情符标注 集;对于情感倾向不明显的表情符,利用种子情感词和已得到的表情符标注集构建模型,实现其情感倾向的自动判定。实验结果表明,本文方法在微博表情符情感倾向的自动判 定上有很好的效果。     

大学生与微博名人准社会交往的实证研究

文章对大学生与微博名人的准社会交往的条件、理念、动机、内容、途径以及成效等进行分析研究,并对相关概念作出界定。研究发现,在大学生与微博名人的准社会交往中呈现出单向度地与微博名人形成了良性交往关系、顺从微博名人价值观念的意愿显著、对微博名人存在超现实评价等现象,与微博名人的准社会交往具有发展性等鲜明特征。文章揭示了互联网环境下微博对大学生成长发展产生的重要影响,同时提出了引导和规范大学生与微博名人准社会交往的对策建议。     

论微博问政对我国政策制定的影响

微博问政的兴起是建立在网络资源的发展上,是公民政治参与的一种新形式。微博问政涉及到政府的各个方面。本文着重探讨微博问政对公共政策制定的影响。在分析微博问政现象产生原因的基础上,从微博自身、公民、政府等不同角度探讨微博问政对政策制定的有利和不利影响。继而探寻一些方法,促使微博问政与公共政策的制定实现良性互动。     

Microblog Summarization via Enriching Contextual Features Based on Sentence-Level Semantic Analysis

A novel microblog summarization approach via enriching contextual features on sentencelevel semantic analysis is proposed in this paper.At first,a Chinese sentential semantic model (CSM) is employed to analyze the semantic structure of each microblog sentence.Then,a combination of sentence-level semantic analysis and latent dirichlet allocation is utilized to acquire extra features and related words to enrich the collection of microblog messages.The simlilarites between the two sentences are calculated based on the enriched features.Finally,the semantic weight and relation weight are calculated to select the most informative sentences,which form the final summary for microblog messages.Experimental results demonstrate the advantages of our proposed approach.The results indicate that introducing sentence-level semantic analysis for context enrichment can better represent sentential semantic.The proposed criteria,namely,semantic weight and relation weight enhance summary result.Furthermore,CSM is a useful framework for sentence-level semantic analysis.     

Commentaries, opinions, and the growth of scientific knowledge.

Comments on J. J. Christensen-Szalanski and L. R. Beach's (see record 1984-21471-001) conclusion that the attention given to commentaries and replies to articles did not justify the extra space and indicates that less than 1% of all the articles that appeared in psychology journals had commentaries. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

甲烷蒸汽转化法制氢工艺评述

介绍甲烷蒸汽转化法制氢技术主要技术提供方及其大型单系列装置建厂业绩，并对制氢装置的工艺设计以及烟气废热和高温转化气热量的利用进行了综述评述。