Democracy, participation and convergent media : case studies in contemporary online news journalism in Australia

The shift from 20th century mass communications media towards convergent media and Web 2.0 has raised the possibility of a renaissance of the public sphere, based around citizen journalism and participatory media culture. This paper will evaluate such claims both conceptually and empirically. At a conceptual level, it is noted that the question of whether media democratization is occurring depends in part upon how democracy is understood, with some critical differences in understandings of democracy, the public sphere and media citizenship. The empirical work in this paper draws upon various case studies of new developments in Australian media, including online- only newspapers, developments in public service media, and the rise of commercially based online alternative media. It is argued that participatory media culture is being expanded if understood in terms of media pluralism, but that implications for the public sphere depend in part upon how media democratization is defined.

Democracy, participation and convergent media : case studies in contemporary online news journalism in Australia

The shift from 20th century mass communications media towards convergent media and Web 2.0 has raised the possibility of a renaissance of the public sphere, based around citizen journalism and participatory media culture. This paper will evaluate such claims both conceptually and empirically. At a conceptual level, it is noted that the question of whether media democratization is occurring depends in part upon how democracy is understood, with some critical differences in understandings of democracy, the public sphere and media citizenship. The empirical work in this paper draws upon various case studies of new developments in Australian media, including online-only newspapers, developments in public service media, and the rise of commercially based online alternative media. It is argued that participatory media culture is being expanded if understood in terms of media pluralism, but that implications for the public sphere depend in part upon how media democratization is defined.

Citizen journalism : a primer :when news takes to the Internet

This paper identifies factors underpinning the emergence of citizen journalism, including the rise of Web 2.0, rethinking journalism as a professional ideology, the decline of ‘high modernist’ journalism, divergence between elite and popular opinion, changing revenue bases for news production, and the decline of deference in democratic societies. It will connect these issues to wider debates about the implications of journalism and news production increasingly going into the Internet environment.

Standing on the shoulders of ants : stigmergy in the Web

Stigmergy is a biological term used when discussing insect or swarm behaviour, and describes a model supporting environmental communication separately from artefacts or agents. This phenomenon is demonstrated in the behavior of ants and their food gathering process when following pheromone trails, or similarly termites and their termite mound building process. What is interesting with this mechanism is that highly organized societies are achieved with a lack of any apparent management structure. Stigmergic behavior is implicit in the Web where the volume of users provides a self-organizing and self-contextualization of content in sites which facilitate collaboration. However, the majority of content is generated by a minority of the Web participants. A significant contribution from this research would be to create a model of Web stigmergy, identifying virtual pheromones and their importance in the collaborative process. This paper explores how exploiting stigmergy has the potential of providing a valuable mechanism for identifying and analyzing online user behavior recording actionable knowledge otherwise lost in the existing web interaction dynamics. Ultimately this might assist our building better collaborative Web sites.

In their own words: Why teenagers don't use social networking sites

We explored common reasons for non-use of the rapidly growing popularity of social networking sites among a sample of Australian adolescents (N = 69). Transcripts were coded by grouping responses along similar themes for non-use that had been commonly stated by participants. The primary reasons offered by adolescents were: lack of motivation, poor use of time, preference for other forms of communication, preference for engaging in other activities, cybersafety concerns, and a dislike of self-presentation online. The identification of these themes allows for a greater understanding of teenagers' decisions not to engage in the popular medium of communication and points to possible strategies that could be utilised by Web site developers in efforts to appeal to a wider teenage audience.

Classifying the user intent of web queries using k-means clustering

Purpose: Web search engines are frequently used by people to locate information on the Internet. However, not all queries have an informational goal. Instead of information, some people may be looking for specific web sites or may wish to conduct transactions with web services. This paper aims to focus on automatically classifying the different user intents behind web queries. Design/methodology/approach: For the research reported in this paper, 130,000 web search engine queries are categorized as informational, navigational, or transactional using a k-means clustering approach based on a variety of query traits. Findings: The research findings show that more than 75 percent of web queries (clustered into eight classifications) are informational in nature, with about 12 percent each for navigational and transactional. Results also show that web queries fall into eight clusters, six primarily informational, and one each of primarily transactional and navigational. Research limitations/implications: This study provides an important contribution to web search literature because it provides information about the goals of searchers and a method for automatically classifying the intents of the user queries. Automatic classification of user intent can lead to improved web search engines by tailoring results to specific user needs. Practical implications: The paper discusses how web search engines can use automatically classified user queries to provide more targeted and relevant results in web searching by implementing a real time classification method as presented in this research. Originality/value: This research investigates a new application of a method for automatically classifying the intent of user queries. There has been limited research to date on automatically classifying the user intent of web queries, even though the pay-off for web search engines can be quite beneficial. © Emerald Group Publishing Limited.

Using the web to look for work: Implications for online job seeking and recruiting

Purpose - The web is now a significant component of the recruitment and job search process. However, very little is known about how companies and job seekers use the web, and the ultimate effectiveness of this process. The specific research questions guiding this study are: how do people search for job-related information on the web? How effective are these searches? And how likely are job seekers to find an appropriate job posting or application? Design/methodology/approach - The data used to examine these questions come from job seekers submitting job-related queries to a major web search engine at three points in time over a five-year period. Findings - Results indicate that individuals seeking job information generally submit only one query with several terms and over 45 percent of job-seeking queries contain a specific location reference. Of the documents retrieved, findings suggest that only 52 percent are relevant and only 40 percent of job-specific searches retrieve job postings. Research limitations/implications - This study provides an important contribution to web research and online recruiting literature. The data come from actual web searches, providing a realistic glimpse into how job seekers are actually using the web. Practical implications - The results of this research can assist organizations in seeking to use the web as part of their recruiting efforts, in designing corporate recruiting web sites, and in developing web systems to support job seeking and recruiting. Originality/value - This research is one of the first studies to investigate job searching on the web using longitudinal real world data. © Emerald Group Publishing Limited.

Using Web Search Logs to Identify Query Classification Terms

Purpose – The work presented in this paper aims to provide an approach to classifying web logs by personal properties of users. Design/methodology/approach – The authors describe an iterative system that begins with a small set of manually labeled terms, which are used to label queries from the log. A set of background knowledge related to these labeled queries is acquired by combining web search results on these queries. This background set is used to obtain many terms that are related to the classification task. The system then ranks each of the related terms, choosing those that most fit the personal properties of the users. These terms are then used to begin the next iteration. Findings – The authors identify the difficulties of classifying web logs, by approaching this problem from a machine learning perspective. By applying the approach developed, the authors are able to show that many queries in a large query log can be classified. Research limitations/implications – Testing results in this type of classification work is difficult, as the true personal properties of web users are unknown. Evaluation of the classification results in terms of the comparison of classified queries to well known age-related sites is a direction that is currently being exploring. Practical implications – This research is background work that can be incorporated in search engines or other web-based applications, to help marketing companies and advertisers. Originality/value – This research enhances the current state of knowledge in short-text classification and query log learning. Classification schemes, Computer networks, Information retrieval, Man-machine systems, User interfaces

Stigmergy in Web 2.0 : a model for site dynamics

Building Web 2.0 sites does not necessarily ensure the success of the site. We aim to better understand what improves the success of a site by drawing insight from biologically inspired design patterns. Web 2.0 sites provide a mechanism for human interaction enabling powerful intercommunication between massive volumes of users. Early Web 2.0 site providers that were previously dominant are being succeeded by newer sites providing innovative social interaction mechanisms. Understanding what site traits contribute to this success drives research into Web sites mechanics using models to describe the associated social networking behaviour. Some of these models attempt to show how the volume of users provides a self-organising and self-contextualisation of content. One model describing coordinated environments is called stigmergy, a term originally describing coordinated insect behavior. This paper explores how exploiting stigmergy can provide a valuable mechanism for identifying and analysing online user behavior specifically when considering that user freedom of choice is restricted by the provided web site functionality. This will aid our building better collaborative Web sites improving the collaborative processes.

The web site and brand trust as antecedents of online loyalty

As online business thrives, a company’s Web presence holds enormous importance as a source of information, entertainment, and customer service for Internet users. Besides being user-friendly, a Web site should offer interesting and enjoyable content to attract online visitors in an ever-changing multimedia environment. Companies that operate globally must know how cultural differences influence the way potential customers perceive their sites. This paper presents a model that highlights the importance of ease of use, enjoyment, content, and brand trust for Web site loyalty. The model is subsequently tested in four countries: Australia, Japan, Mongolia, and the USA. The results show that perceptual differences exist: while ease of use is crucial for Web site loyalty in all four countries, the importance of content, perceived enjoyment, and brand trust varies across different cultures.

Modelling web-server Flash Events

A Flash Event (FE) represents a period of time when a web-server experiences a dramatic increase in incoming traffic, either following a newsworthy event that has prompted users to locate and access it, or as a result of redirection from other popular web or social media sites. This usually leads to network congestion and Quality-of-Service (QoS) degradation. These events can be mistaken for Distributed Denial-of-Service (DDoS) attacks aimed at disrupting the server. Accurate detection of FEs and their distinction from DDoS attacks is important, since different actions need to be undertaken by network administrators in these two cases. However, lack of public domain FE datasets hinders research in this area. In this paper we present a detailed study of flash events and classify them into three broad categories. In addition, the paper describes FEs in terms of three key components: the volume of incoming traffic, the related source IP-addresses, and the resources being accessed. We present such a FE model with minimal parameters and use publicly available datasets to analyse and validate our proposed model. The model can be used to generate different types of FE traffic, closely approximating real-world scenarios, in order to facilitate research into distinguishing FEs from DDoS attacks.

Extending Web Modeling Language to exploit stigmergy : intentionally recording unintentional trails

Software development and Web site development techniques have evolved significantly over the past 20 years. The relatively young Web Application development area has borrowed heavily from traditional software development methodologies primarily due to the similarities in areas of data persistence and User Interface (UI) design. Recent developments in this area propose a new Web Modeling Language (WebML) to facilitate the nuances specific to Web development. WebML is one of a number of implementations designed to enable modeling of web site interaction flows while being extendable to accommodate new features in Web site development into the future. Our research aims to extend WebML with a focus on stigmergy which is a biological term originally used to describe coordination between insects. We see design features in existing Web sites that mimic stigmergic mechanisms as part of the UI. We believe that we can synthesize and embed stigmergy in Web 2.0 sites. This paper focuses on the sub-topic of site UI design and stigmergic mechanism designs required to achieve this.

Cross-cultural language learning and web design complexity

Accepting the fact that culture and language are interrelated in second language learning (SLL), the web sites should be designed to integrate with the cultural aspects. Yet many SLL web sites fail to integrate with the cultural aspects and/or focus on language acquisition only. This study identified three issues: (1) anthropologists’ cultural models mostly adopted in cross-cultural web user interface have been superficially used; (2) web designers deal with culture as a fixed one which needs to be modeled into interface design elements, so (3) there is a need for a communication framework between educators and design practitioners, which can be utilized in web design processes. This paper discusses what anthropology can contribute to language learning, mediated through web design processes and suggests a cultural user experience framework for web-based SLL by presenting an exemplary matrix. To evaluate the effectiveness of the framework, the key stakeholders (learners, teachers, and designers) participated in a case scenario-based evaluation. The result shows a high possibility that the framework can enhance the effective communication and collaboration for the cultural integration.

Hot topic detection in news blogs from the perspective of W2T

News blog hot topics are important for the information recommendation service and marketing. However, information overload and personalized management make the information arrangement more difficult. Moreover, what influences the formation and development of blog hot topics is seldom paid attention to. In order to correctly detect news blog hot topics, the paper first analyzes the development of topics in a new perspective based on W2T (Wisdom Web of Things) methodology. Namely, the characteristics of blog users, context of topic propagation and information granularity are unified to analyze the related problems. Some factors such as the user behavior pattern, network opinion and opinion leader are subsequently identified to be important for the development of topics. Then the topic model based on the view of event reports is constructed. At last, hot topics are identified by the duration, topic novelty, degree of topic growth and degree of user attention. The experimental results show that the proposed method is feasible and effective.

Extracting news blog hot topics based on the W2T methodology

Although topic detection and tracking techniques have made great progress, most of the researchers seldom pay more attention to the following two aspects. First, the construction of a topic model does not take the characteristics of different topics into consideration. Second, the factors that determine the formation and development of hot topics are not further analyzed. In order to correctly extract news blog hot topics, the paper views the above problems in a new perspective based on the W2T (Wisdom Web of Things) methodology, in which the characteristics of blog users, context of topic propagation and information granularity are investigated in a unified way. The motivations and features of blog users are first analyzed to understand the characteristics of news blog topics. Then the context of topic propagation is decomposed into the blog community, topic network and opinion network, respectively. Some important factors such as the user behavior pattern, opinion leader and network opinion are identified to track the development trends of news blog topics. Moreover, a blog hot topic detection algorithm is proposed, in which news blog hot topics are identified by measuring the duration, topic novelty, attention degree of users and topic growth. Experimental results show that the proposed method is feasible and effective. These results are also useful for further studying the formation mechanism of opinion leaders in blogspace.