Twitter data: what do they represent?

Scholarly research into the uses of social media has become a major area of growth in recent years, as the adoption of social media for public communication itself has continued apace. While social media platforms provide ready avenues for data access through their Application Programming interfaces, it is increasingly important to think through exactly what these data represent, and what conclusions about the role of social media in society the research which is based on such data therefore enables. This article explores these issues especially for one of the currently leading social media platforms: Twitter.

Locality-sensitive hashing for protein classification

Determination of sequence similarity is a central issue in computational biology, a problem addressed primarily through BLAST, an alignment based heuristic which has underpinned much of the analysis and annotation of the genomic era. Despite their success, alignment-based approaches scale poorly with increasing data set size, and are not robust under structural sequence rearrangements. Successive waves of innovation in sequencing technologies – so-called Next Generation Sequencing (NGS) approaches – have led to an explosion in data availability, challenging existing methods and motivating novel approaches to sequence representation and similarity scoring, including adaptation of existing methods from other domains such as information retrieval. In this work, we investigate locality-sensitive hashing of sequences through binary document signatures, applying the method to a bacterial protein classification task. Here, the goal is to predict the gene family to which a given query protein belongs. Experiments carried out on a pair of small but biologically realistic datasets (the full protein repertoires of families of Chlamydia and Staphylococcus aureus genomes respectively) show that a measure of similarity obtained by locality sensitive hashing gives highly accurate results while offering a number of avenues which will lead to substantial performance improvements over BLAST..

Exploring the impact of shared domain knowledge on strategic alignment in the Australian public sector

In this age of ever-increasing information technology (IT) driven environments, governments/or public sector organisations (PSOs) are expected to demonstrate the business value of the investment in IT and take advantage of the opportunities offered by technological advancements. Strategic alignment (SA) emerged as a mechanism to bridge the gap between business and IT missions, objectives, and plans in order to ensure value optimisation from investment in IT and enhance organisational performance. However, achieving and sustaining SA remains a challenge requiring even more agility nowadays to keep up with turbulent organisational environments. The shared domain knowledge (SDK) between the IT department and other diverse organisational groups is considered as one of the factors influencing the successful implementation of SA. However, SDK in PSOs has received relatively little empirical attention. This paper presents findings from a study which investigated the influence of SDK on SA within organisations in the Australian public sector. The developed research model examined the relationship of SDK between business and IT domains with SA using a survey of 56 public sector professionals and executives. A key research contribution is the empirical demonstration that increasing levels of SDK between IT and business groups leads to increased SA.

Aspect-based opinion extraction from customer reviews

Text is the main method of communicating information in the digital age. Messages, blogs, news articles, reviews, and opinionated information abounds on the Internet. People commonly purchase products online and post their opinions about purchased items. This feedback is displayed publicly to assist others with their purchasing decisions, creating the need for a mechanism with which to extract and summarize useful information for enhancing the decision-making process. Our contribution is to improve the accuracy of extraction by combining different techniques from three major areas, named Data Mining, Natural Language Processing techniques and Ontologies. The proposed framework sequentially mines product’s aspects and users’ opinions, groups representative aspects by similarity, and generates an output summary. This paper focuses on the task of extracting product aspects and users’ opinions by extracting all possible aspects and opinions from reviews using natural language, ontology, and frequent “tag” sets. The proposed framework, when compared with an existing baseline model, yielded promising results.

Component modeling for SCADA network mapping

Supervisory Control and Data Acquisition systems (SCADA) are widely used to control critical infrastructure automatically. Capturing and analyzing packet-level traffic flowing through such a network is an essential requirement for problems such as legacy network mapping and fault detection. Within the framework of captured network traffic, we present a simple modeling technique, which supports the mapping of the SCADA network topology via traffic monitoring. By characterizing atomic network components in terms of their input-output topology and the relationship between their data traffic logs, we show that these modeling primitives have good compositional behaviour, which allows complex networks to be modeled. Finally, the predictions generated by our model are found to be in good agreement with experimentally obtained traffic.

Identifying product families using data mining techniques in manufacturing paradigm

Identifying product families has been considered as an effective way to accommodate the increasing product varieties across the diverse market niches. In this paper, we propose a novel framework to identifying product families by using a similarity measure for a common product design data BOM (Bill of Materials) based on data mining techniques such as frequent mining and clus-tering. For calculating the similarity between BOMs, a novel Extended Augmented Adjacency Matrix (EAAM) representation is introduced that consists of information not only of the content and topology but also of the fre-quent structural dependency among the various parts of a product design. These EAAM representations of BOMs are compared to calculate the similarity between products and used as a clustering input to group the product fami-lies. When applied on a real-life manufacturing data, the proposed framework outperforms a current baseline that uses orthogonal Procrustes for grouping product families.

Suggestions for the next wave of BPM research : strengthening the theoretical core and exploring the protective belt

In this essay, I present a reflective and generative analysis of Business Process Management research, in which I analyze process management and the surrounding research program from the viewpoint of a theoretical paradigm embracing analytical, empirical, explanatory and design elements. I argue that this view not only reconciles different perceptions of BPM and different research streams, but that it also informs ways in which the BPM research program could develop into a much richer, more inclusive and overall more significant body of work than it has to date. I define three perspectives on a BPM research agenda, give several examples of exciting existing research, and offer key opportunities for further research that can (a) strengthen the core of BPM, (b) generate novel theory from BPM in relevant and topical big issue domains, and (c) explore more rigorously and comprehensively the protective belt of BPM assumptions that much of the present research abides by. The essay ends with some recommendations for continuing the debate about what constitutes BPM and some suggestions for how future research in this area might be carried out.

E-health: potential benefits and challenges in providing and accessing sexual health services

BACKGROUND: E-health has become a burgeoning field in which health professionals and health consumers create and seek information. E-health refers to internet-based health care and information delivery and seeks to improve health service locally, regionally and worldwide. E-sexual health presents new opportunities to provide online sexual health services irrespective of gender, age, sexual orientation and location. DISCUSSION: The paper used the dimensions of the RE-AIM model (reach, efficacy, adoption, implementation and maintenance) as a guiding principle to discuss potentials of E-health in providing and accessing sexual health services. There are important issues in relation to utilising and providing online sexual health services. For healthcare providers, e-health can act as an opportunity to enhance their clients' sexual health care by facilitating communication with full privacy and confidentiality, reducing administrative costs and improving efficiency and flexibility as well as market sexual health services and products. Sexual health is one of the common health topics which both younger and older people explore on the internet and they increasingly prefer sexual health education to be interactive, non-discriminate and anonymous. This commentary presents and discusses the benefits of e-sexual health and provides recommendations towards addressing some of the emerging challenges. FUTURE DIRECTIONS: The provision of sexual health services can be enhanced through E-health technology. Doing this can empower consumers to engage with information technology to enhance their sexual health knowledge and quality of life and address some of the stigma associated with diversity in sexualities and sexual health experiences. In addition, e-sexual health may better support and enhance the relationship between consumers and their health care providers across different locations. However, a systematic and focused approach to research and the application of findings in policy and practice is required to ensure that E-health benefits all population groups and the information is current and clinically valid and effective, including preventative approaches for various client groups with diverse needs.

Seeking better IT value conceptualization : some meta-theoretical considerations

Information Technology (IT) value is amongst the most important concepts in the Information Systems (IS) research field. Yet, a clear, well-formulated conceptualization of IT value, cumulatively built upon, is lacking. Drawing from the Facet Theory literature, this paper broaches several meta-theoretical considerations addressing an “ideal” conceptualization of IT value. We argue these considerations may shed light on the advancement of IT value conceptualization methodology.

A case study of utilising concept knowledge in a topic specific document collection

The use of ‘topic’ concepts has shown improved search performance, given a query, by bringing together relevant documents which use different terms to describe a higher level concept. In this paper, we propose a method for discovering and utilizing concepts in indexing and search for a domain specific document collection being utilized in industry. This approach differs from others in that we only collect focused concepts to build the concept space and that instead of turning a user’s query into a concept based query, we experiment with different techniques of combining the original query with a concept query. We apply the proposed approach to a real-world document collection and the results show that in this scenario the use of concept knowledge at index and search can improve the relevancy of results.

Transforming the core business of teaching and learning in classrooms through ICT

Information and Communication Technology (ICT) has become an integral part of societies across the globe. This study demonstrates how successful technology integration by 10 experienced teachers in an Australian high school was dependent on teacher-driven change and innovation that influenced the core business of teaching and learning. The teachers were subject specialists across a range of disciplines, engaging their Year Eight students (aged 12–14 years) in the Technology Rich Classrooms programme. Two classrooms were renovated to accommodate the newly acquired computer hardware. The first classroom adopted a one-to-one desktop model with all the computers with Internet access arranged in a front-facing pattern. The second classroom had computers arranged in small groups. The students also used Blackboard to access learning materials after school hours. Qualitative data were gathered from teachers mainly through structured and unstructured interviews and a range of other approaches to ascertain their perceptions of the new initiative. This investigation showed that ICT was impacting positively on the core business of teaching and learning. Through the support of the school leadership team, the built environment was enabling teachers to use ICT. This influenced their pedagogical approaches and the types of learning activities they designed and implemented. As a consequence, teachers felt that students were motivated and benefited through this experience.

The application of social network analysis in the construction industry of Hong Kong

The Hong Kong construction industry is currently facing ageing problem and labour shortage. There are opportunities for employing ethnic minority construction workers to join this hazardous industry. These ethnic minority workers are prone to accidents due to communication barriers. Safety communication is playing an important role for avoiding the accidents on construction sites. However, the ethnic minority workers are not very fluent in the local language and facing safety communication problems while working with local workers. Social network analysis (SNA), being an effective tool to identify the safety communication flow on the construction site, is used to attain the measures of safety communication like centrality, density and betweenness within the ethnic minorities and local workers, and to generate sociograms that visually represent communication pattern within the effective and ineffective safety networks. The aim of this paper is to present the application of SNA for improving the safety communication of ethnic minorities in the construction industry of Hong Kong. The paper provides the theoretical background of SNA approaches for the data collection and analysis using the software UCINET and NetDraw, to determine the predominant safety communication network structure and pattern of ethnic minorities on site.