基于微博客的竞争情报搜集研究:以新浪微博为例

微博客的出现给竞争情报搜集工作提供了新的信息源。国内微博客产品发展迅速,本文选取新浪微博客为研究环境,分析了其独特的信息架构和信息传播模式,认为竞争情报工作者可以通过关注竞争对手、TAG标签、App应用、内容搜索、内容订阅、人际情报网络等六种方法和工具在微博客环境下有效地开展情报搜集工作,并结合实际案例分别对这些方法和工具进行了说明。本文对于竞争情报工作者在新浪微博客这一新型信息源中开展情报搜集活动有一定的指导意义。     

A user term visualization analysis based on a social question and answer log

The authors of this paper investigate terms of consumers’ diabetes based on a log from the Yahoo!Answers social question and answers (Q&A) forum, ascertain characteristics and relationships among terms related to diabetes from the consumers’ perspective, and reveal users’ diabetes information seeking patterns. In this study, the log analysis method, data coding method, and visualization multiple-dimensional scaling analysis method were used for analysis. The visual analyses were conducted at two levels: terms analysis within a category and category analysis among the categories in the schema. The findings show that the average number of words per question was 128.63, the average number of sentences per question was 8.23, the average number of words per response was 254.83, and the average number of sentences per response was 16.01. There were 12 categories (Cause & Pathophysiology, Sign & Symptom, Diagnosis & Test, Organ & Body Part, Complication & Related Disease, Medication, Treatment, Education & Info Resource, Affect, Social & Culture, Lifestyle, and Nutrient) in the diabetes related schema which emerged from the data coding analysis. The analyses at the two levels show that terms and categories were clustered and patterns were revealed. Future research directions are also included.     

Understanding the formation mechanism of high-quality knowledge in social question and answer communities: A knowledge co-creation perspective

The social question and answer (Q&A) community provides people with an effective tool to obtain high-quality information. From the perspective of reciprocal determinism and value co-creation, this study aims to investigate the formation mechanism of high-quality knowledge in the community. We develop a model to investigate how cognitive factors and community technological factors influence users’ knowledge co-creation behavior, thereby influencing knowledge quality in the community. A survey of 382 knowledge contributors in a social Q&A community shows that knowledge self-efficacy, topic richness, personalized recommendation, and social interactivity have a positive impact on users' knowledge sharing and integration behavior, which subsequently affect the community’s knowledge quality. Moreover, users' ratings moderate the influence of knowledge sharing on knowledge quality. This research demonstrates the synergistic effect of people and technology in knowledge co-creation, thus advances literature about value co-creation and content quality in online communities.     

基于马尔可夫链的政府负面网络舆情热度趋势分析--以新浪微博为例

微博作为用户关系信息分享、传播以及获取的平台,由于信息量大、传播更迅速,成为网络舆情传播的主要载体。在查阅大量文献的基础上,首先对政府负面网络舆情事件热度进行明确界定与度量,之后通过划分状态空间、构建状态转移矩阵、开展舆情热度趋势预测等步骤建立基于马尔科夫链的政府负面网络舆情热度趋势预测模型。以新浪微博为例,选取2013年度的舆情热点事件“延安城管暴力执法”进行舆情热度实证分析,验证了模型的合理性和有效性,进而为政府开展网络舆情管理和网络危机公关活动、合理引导舆情事态发展提供理论依据。     

Microcollaborations in a social Q&A community

Most social Q&A sites are designed to support solo searchers who access the aggregated opinions of other users, and ask and answer questions of their own. The purpose of this paper is to show how users in one social Q&A community defy system constraints to engage in brief, informal episodes of collaborative information seeking called microcollaborations. A brief literature review is presented, suggesting a view of information seeking as a combination of problem-centered information seeking, technological affordances and constraints, and social and affective factors. The results of content and transaction log analyses of user interactions suggest that topics of collaboration share a common threshold of complexity and invite responses containing both fact and opinion. Analysis also revealed that key elements in predicting a collaborative instance involve social capital and affective factors unrelated to the topic of the collaboration. Suggestions for supporting future lightweight microcollaborations, and implications for future research, are discussed.     

Characterizing multi-domain false news and underlying user effects on Chinese Weibo

False news that spreads on social media has proliferated over the past years and has led to multi-aspect threats in the real world. While there are studies of false news on specific domains (like politics or health care), little work is found comparing false news across domains. In this article, we investigate false news across nine domains on Weibo, the largest Twitter-like social media platform in China, from 2009 to 2019. The newly collected data comprise 44,728 posts in the nine domains, published by 40,215 users, and reposted over 3.4 million times. Based on the distributions and spreads of the multi-domain dataset, we observe that false news in domains that are close to daily life like health and medicine generated more posts but diffused less effectively than those in other domains like politics, and that political false news had the most effective capacity for diffusion. The widely diffused false news posts on Weibo were associated strongly with certain types of users — by gender, age, etc. Further, these posts provoked strong emotions in the reposts and diffused further with the active engagement of false-news starters. Our findings have the potential to help design false news detection systems in suspicious news discovery, veracity prediction, and display and explanation. The comparison of the findings on Weibo with those of existing work demonstrates nuanced patterns, suggesting the need for more research on data from diverse platforms, countries, or languages to tackle the global issue of false news. The code and new anonymized dataset are available at https://github.com/ICTMCG/Characterizing-Weibo-Multi-Domain-False-News.     

基于案例分析的国外在华“微传播”政府应对研究--以新浪微博为例

以国外政府机构和政要入驻新浪微博的典型案例为研究对象,利用内容分析法和案例分析法,探析国外在华“微传播”现象并总结相应政府应对策略。研究发现,国外政府机构和政要善用自媒体社交工具展开全方位的信息传播与价值输出,对此,我国一方面要关注、警惕,另一方面也要学习、借鉴。     

Social influence on endorsement in social Q&A community: Moderating effects of temporal and spatial factors

This study examines the impacts of social influence, which are manifested by popularity and source credibility, on social endorsement in social Q&A community; and how the relationship is impacted by temporal-spatial factors. By collecting panel data from a large platform, the results of an econometric model demonstrate that popularity and source credibility are positively associated with social endorsement. With respect to the moderation effects, the results further show that time distance strengthens the effect of popularity on the social endorsement, but undermines the effect of source credibility; while crowdedness plays the role that strengthens the impact of popularity on the social endorsement, it has no significant moderating effect on the relationship between source credibility and social endorsement. Both theoretical and practical implications are discussed.     

Workers united: Digitally enhancing social connectedness on the shop floor

Organizations increasingly implement processes-oriented setups like value stream production. Whereas this transition may bring many advantages on an organizational level, related studies show that shop floor workers feel less able to maintain close contact with others and exchange awareness cues. Their diminished social connectedness has consequences on the personal (e.g., reduced satisfaction) and organizational (reduced efficiency) level. The current wave of digitization brings ample opportunities for companies to bring their employees closer together again. In order to identify such opportunities, we have studied the shop floor production practices of an automotive OEM (original equipment manufacturer) for nearly two years. Following a scenario-based action design science approach, we have developed problem and activity scenarios as well as a prototype that helps the workers to improve their social connectedness in three different scenarios. Eight weeks of use demonstrated the prototype’s positive impact on the employees’ social connectedness by allowing for social appraisal and by improving their sense of sharing and involvement. Our results show which information technology (IT) design elements can contribute to social connectedness on the shop floor.     

Applying a multi-dimensional hedonic concept of intrinsic motivation on social tagging tools: A theoretical model and empirical validation

Participation in and adding content to social tagging tools is important for these tools to achieve their purpose of classifying and organizing information. Users of social tagging tools are driven to participate and add tags by extrinsic and intrinsic motivation. Extrinsic motivation is dominating research as a main predictor of why users use information systems. Social tagging tools, as a subset of social media tools, are distinguished by their unique social aspect that makes intrinsic motivation a potential driver for users to add tags to content. Intrinsic motivation, when applied to social tagging tools, could entail many shades that represent different users’ motives for using such tools. In this paper, we add a rich concept of intrinsic motivation to include hedonism as a main predictor of users’ behavior on social tagging tools. We empirically validate a previously proposed theoretical model of three dimensional concepts of hedonism with three components describing individuals’ hedonic state when interacting with social tagging tools: explorability, curiosity, and enjoyment. After a robust and thorough data analysis using structured equation modeling, the results confirm our theoretical model and suggest using a richer concept of enjoyment to reflect a hedonic dimension when investigating intrinsic motivation with interactive social media tools. Our validated model could be the spark of new factors that have the potential to influence user acceptance of information systems in general and in social media tools. This research contributes to the development of attitude-behavior theories that could explain users’ acceptance of dynamic web     

基于问答（Q＆A）系统原理的WAP信息检索

移动网络为人们提供了越来越丰富的信息服务，然而，这些面向移动终端的信息服务却缺少一个有效的信息检索途径，即用户无法对这些海量的信息进行快速、方便的检索以满足信息使用要求。本文以此为问题出发点．提出了基干问答（Q＆A）原理的WAP信息检索方案，并就其如何解决无线网络信息检索问题进行了相关论述．     

Information avoidance behavior on social network sites: Information irrelevance,overload, and the moderating role of time pressure

Drawing on the stressor-strain-outcome framework, this study investigates how information irrelevance and overload induce social network fatigue, and the relationship of these variables to users’ information avoidance behavior. It also examines the conditions under which social network fatigue is more likely to be translated into information avoidance behavior. The analysis of data collected from 341 users of WeChat Moments suggests that information irrelevance directly leads to information avoidance behavior, and social media fatigue as a mediator partially mediates the impact of information overload on information avoidance behavior and fully mediates the impact of social overload on information avoidance behavior. Furthermore, time pressure strengthens the effect of social network fatigue on information avoidance behavior. This study fulfills the identified need for an in-depth investigation of actual discontinuous behavior in social network services (SNSs) by investigating information avoidance behavior and its antecedents. The findings provide SNSs providers with guidelines on how to manage users’ behavior so that they remain active users of the SNSs.     

高校学生微博使用行为大数据分析和管理研究

微博作为信息时代的重要社交工具,得到了高校学生的普遍欢迎。大学生微博使用行为的信息挖掘,对于观察大学生群体社交行为特点,促进高校大学生线上行为管理具有重要的实践意义。本文结合统计调查和软件技术的方式,对高校学生的基本信息、微博内容、评论情况、关注焦点等进行数据采集和分类统计,判断其情感倾向和微博舆论特点。通过对采集大数据的分析研究,从客观上了解高校学生的微博使用行为习惯、使用态度和使用需求,做出规律总结与趋势预测,为高校大学生的微博行为引导和高校舆情管理提供参考意见。     

Fields and pathways: Contrasting or complementary views of information seeking

This research contrasts two different conceptions, fields and pathways, of individual information behavior in context. These different approaches imply different relationships between actors and their information environments and, thus, encapsulate different views of the relationship between individual actions and contexts. We discuss these different theoretical views, then empirically compare and contrast them. The operationalization of these conceptions is based on different analytic treatments of the same raw data: a battery of three questions based on respondent’s unaided recall of the sources they would consult for information on inherited cancers, a particularly rich information seeking problem. These operationalizations are then analyzed in a nomological network of related concepts drawn from an omnibus survey of 882 adults. The results indicated four clusters for fields and 16 different pathways, indicating increased fragmentation of information environments, with different underlying logics and active ingredients, although the use of the Internet appears to be an emerging common theme. The analysis of the nomological network suggests that both approaches may have applications for particular problems. In the implications, we compare and contrast these approaches, discussing their significance for future methodological, analytical, and theoretical developments.     

Visualization of the Nordic academic web: Link analysis using social network tools

The aim of this paper is to study the link relationships in the Nordic academic web space – comprised of 23 Finnish, 11 Danish and 28 Swedish academic web domains with the European one. Through social networks analysis we intend to detect sub-networks within the Nordic network, the position and role of the different university web domains and to understand the structural topology of this web space. Co-link analysis, with asymmetrical matrices and cosine measure, is used to identify thematic clusters. Results show that the Nordic network is a cohesive network, set up by three well-defined sub-networks and it rests on the Finnish and Swedish sub-networks. We conclude that the Danish network has less visibility than other Nordic countries. The Swedish one is the principal Nordic sub-network and the Finland network is a slightly isolated from Europe, with the exception of the University of Helsinki.     

Why users keep answering questions in online question answering communities: A theoretical and empirical investigation

This study theorized and validated a model of knowledge sharing continuance in a special type of online community, the online question answering (Q&A) community, in which knowledge exchange is reflected mainly by asking and answering specific questions. We created a model that integrated knowledge sharing factors and knowledge self-efficacy into the expectation confirmation theory. The hypotheses derived from this model were empirically validated using an online survey conducted among users of a famous online Q&A community in China, “Yahoo! Answers China”. The results suggested that users’ intention to continue sharing knowledge (i.e., answering questions) was directly influenced by users’ ex-post feelings as consisting of two dimensions: satisfaction, and knowledge self-efficacy. Based on the obtained results, we also found that knowledge self-efficacy and confirmation mediated the relationship between benefits and satisfaction.     

Uncertainty in information seeking and retrieval: A study in an academic environment

This research focuses specifically on uncertainty and information seeking in a digital environment. In this research we argue that different types of uncertainty are associated with the information seeking process and that, with the proliferation of new and different search tools, sources and channels, uncertainty, positive/desirable or negative/undesirable, continues to be a significant factor in the search process. Users may feel uncertain at any stage of the information search and retrieval process and uncertainty may remain even after completion of the process resulting in what may be called persistent uncertainty. An online questionnaire was used to collect data from users in the higher education sector. There were three parts to the questionnaire focusing on: information seeking activities, information seeking problems, and access to specific information channels or sources. Quantitative analysis was carried out on the data collected through the online questionnaire. A total of 668 responses were returned from the chosen user categories of academic staff, research staff and research students. This research has shown that there are some information seeking activities and information seeking problems that are the most common causes of uncertainty among significant number of users from different disciplines, age, gender, ICT skills, etc. This is also the case with respect to access to and use of specific information sources/channels, although the degrees of uncertainty in relation are relatively small. Possible implications of this study and further research issues are indicated.     

Characterising and evaluating information seeking behaviour in a digital environment: Spotlight on the ‘bouncer’

The paper delineates and explains an emerging, but significant, form of digital information seeking behaviour among information consumers, which the authors have called ‘bouncing’. The evidence for this behaviour has emerged from five years of deep log analysis studies – an advanced form of transaction log analysis – of a wide range of users of digital information resources. Much of the evidence and discussion provided comes from the scholarly communication field. Two main bouncing metrics were applied in the log studies: site penetration, which is the number of items or pages viewed in a session, and return visits. The evidence shows that (1) a high proportion of people view just a few items or pages during a visit to a site and, (2) a high proportion of visitors either do not come back to the site or they did so infrequently. Typically those who penetrated a site least tended to return the least frequently. These people are termed ‘bouncers’. They bounce into the site and then bounce out again, presumably, to another site, as a high proportion of them do not appear to come back again. Possible explanations – negative and positive, for the form of behaviour are discussed.     

SocConnect: A personalized social network aggregator and recommender

Users of Social Networking Sites (SNSs) like Facebook, LinkedIn or Twitter, are facing two problems: (1) it is difficult for them to keep track of their social friendships and friends’ social activities scattered across different SNSs; and (2) they are often overwhelmed by the huge amount of social data (friends’ updates and other activities). To address these two problems, we propose a user-centric system called “SocConnect” (Social Connect) for aggregating social data from different SNSs and allowing users to create personalized social and semantic contexts for their social data. Users can blend and group friends on different SNSs, and rate the friends and their activities as favourite, neutral or disliked. SocConnect then provides personalized recommendation of friends’ activities that may be interesting to each user, using machine learning techniques. A prototype is also implemented to demonstrate these functionalities of SocConnect. Evaluation on real users confirms that users generally like the proposed functionalities of our system, and machine learning can be effectively applied to provide personalized recommendation of friends’ activities and help users deal with cognitive overload.     

Building Guanxi network in the mobile social platform: A social capital perspective

Mobile social platform such as WeChat Moments has gained great popularity in China in the past few years. However, there are still a lack of studies that focus on Guanxi network building in the virtual social community. Drawing upon social capital theory and technology affordance theory, this study develops a research model to examine the influences of platform media richness and interactivity on users’ social capital and participation behaviors in the WeChat Moments. An empirical survey was conducted in China and 287 valid data were collected from WeChat users. Structural equation modelling analysis was used to test the research model. The empirical results suggest that platform interactivity and media richness are significant technology affordances that promote users’ Guanxi network, and their influences are mediated by social interaction and shared understanding. Furthermore, Guanxi network is positively associated with users’ active participation in the WeChat Moments. Theoretical and practical implications are illustrated in the final section.