Search results

The purpose of this paper is to present a Big Data solution as a methodological approach to the automated collection, cleaning, collation, and mapping of multimodal, longitudinal data sets from social media. The paper constructs social information landscapes (SIL).

The research presented here adopts a Big Data methodological approach for mapping user-generated contents in social media. The methodology and algorithms presented are generic, and can be applied to diverse types of social media or user-generated contents involving user interactions, such as within blogs, comments in product pages, and other forms of media, so long as a formal data structure proposed here can be constructed.

The limited presentation of the sequential nature of content listings within social media and Web 2.0 pages, as viewed on web browsers or on mobile devices, do not necessarily reveal nor make obvious an unknown nature of the medium; that every participant, from content producers, to consumers, to followers and subscribers, including the contents they produce or subscribed to, are intrinsically connected in a hidden but massive network. Such networks when mapped, could be quantitatively analysed using social network analysis (e.g. centralities), and the semantics and sentiments could equally reveal valuable information with appropriate analytics. Yet that which is difficult is the traditional approach of collecting, cleaning, collating, and mapping such data sets into a sufficiently large sample of data that could yield important insights into the community structure and the directional, and polarity of interaction on diverse topics. This research solves this particular strand of problem.

The automated mapping of extremely large networks involving hundreds of thousands to millions of nodes, encapsulating high resolution and contextual information, over a long period of time could possibly assist in the proving or even disproving of theories. The goal of this paper is to demonstrate the feasibility of using automated approaches for acquiring massive, connected data sets for academic inquiry in the social sciences.

The methods presented in this paper, together with the Big Data architecture can assist individuals and institutions with a limited budget, with practical approaches in constructing SIL. The software-hardware integrated architecture uses open source software, furthermore, the SIL mapping algorithms are easy to implement.

The majority of research in the literature uses traditional approaches for collecting social networks data. Traditional approaches can be slow and tedious; they do not yield adequate sample size to be of significant value for research. Whilst traditional approaches collect only a small percentage of data, the original methods presented here are able to collect and collate entire data sets in social media due to the automated and scalable mapping techniques.

This paper sets out to address the issue of the impact and evolution of digital libraries and information services using the concept of information ecologies.

After setting the perspective, digital libraries are explored from their functional logic inside the social subsystem that deals with transferring knowledge in the form of information among people and generations. The current landscape is then presented, which is complicated by the enormous technological shift in course. The concept of information ecology is useful for reducing this complexity.

Trends affecting modern information ecology in which digital libraries are evolving are studied. Specifically, eight noteworthy processes in this development are analyzed: ubiquity of information management; digital convergence; technological standardization and leverage; the surging of a worldwide space of collaboration, and competition; swift advances in the international division of informational work; the transformation of the physical information units toward the provision of proximity services; the entry of new agents in the field; and the growing emphasis on data management.

The changing environment in the libraries field is explored using the concept of information ecologies. Some of the most important trends in the digital environment are identified and their effect on the social and economical functions of libraries is shown. Information ecology is very complex, with many actors, and libraries have some niches ensured (heritage preservation, proximity services …), though others could be better performed by emerging full‐digital organizations.

The paper aims to explore the value of various notions of precarity for the study of information practices and for addressing inequities and marginalization from an information standpoint.

Several interrelated conceptualizations of precarity and associated terms from outside of library and information science (LIS) are presented. LIS studies involving precarity and related topics, including various situations of insecurity, instability, migration and transition, are then discussed. In that context, new approaches to information precarity and new directions for information practices research are explored.

Studies that draw from holistic characterizations of precarity, especially those engaging with theories from beyond the field, are quite limited in LIS research. Broader understandings of precarity in information contexts may contribute to greater engagement with political and economic considerations and to development of non-individualistic responses and services.

The presentation of a framework for an initial model of information precarity and the expansion of connections between existing LIS research and concepts of precarity from other fields suggest a new lens for further addressing inequities, marginalization and precarious life in LIS research.

The purpose of this paper is to explore the formation, maintenance and disintegration of a fringe Twitter community in order to understand if offline community structure applies to online communities.

The research adopted Big Data methodological approaches in tracking user-generated contents over a series of months and mapped online Twitter interactions as a multimodal, longitudinal “social information landscape”. Centrality measures were employed to gauge the importance of particular user nodes within the complete network and time-series analysis were used to track ego centralities in order to see if this particular online communities were maintained by specific egos.

The case study shows that communities with distinct boundaries and memberships can form and exist within Twitter’s limited user content and sequential policies, which unlike other social media services, do not support formal groups, demonstrating the resilience of desperate online users when their ideology overcome social media limitations. Analysis in this paper using social networks approaches also reveals that communities are formed and maintained from the bottom-up.

The research data is based on a particular data set which occurred within a specific time and space. However, due to the rapid, polarising group behaviour, growth, disintegration and decline of the online community, the data set presents a “laboratory” case from which many other online community can be compared with. It is highly possible that the case can be generalised to a broader range of communities and from which online community theories can be proved/disproved.

The paper showed that particular group of egos with high activities, if removed, could entirely break the cohesiveness of the community. Conversely, strengthening such egos will reinforce the community strength. The questions mooted within the paper and the methodology outlined can potentially be applied in a variety of social science research areas. The contribution to the understanding of a complex social and political arena, as outlined in the paper, is a key example of such an application within an increasingly strategic research area – and this will surely be applied and developed further by the computer science and security community.

The majority of researches that cover these domains have not focused on communities that are multimodal and longitudinal. This is mainly due to the challenges associated with the collection and analysis of continuous data sets that have high volume and velocity. Such data sets are therefore unexploited with regards to cyber-community research.

The purpose of this paper is to investigate political influential spreaders in Twitter at the juncture before and after the Malaysian General Election in 2013 (MGE2013) for the purpose of understanding if the political sphere within Twitter reflects the intentions, popularity and influence of political figures in the year in which Malaysia has its first “social media election.”

A Big Data approach was used for acquiring a series of longitudinal data sets during the election period. The work differs from existing methods focusing on the general statistics of the number of followers, supporters, sentiment analysis, etc. A retweeting network has been extracted from tweets and retweets and has been mapped to a novel information flow and propagation network we developed. The authors conducted quantitative studies using k-shell decomposition, which enables the construction of a quantitative Twitter political propagation sphere where members posited at the core areas are more influential than those in the outer circles and periphery.

The authors conducted a comparative study of the influential members of Twitter political propagation sphere on the election day and the day after. The authors found that representatives of political parties which are located at the center of the propagation network are winners of the presidential election. This may indicate that influential power within Twitter is positively related to the final election results, at least in MGE2013. Furthermore, a number of non-politicians located at the center of the propagation network also significantly influenced the election.

This research is based on a large electoral campaign in a specific election period, and within a predefined nation. While the result is significant and meaningful, more case studies are needed for generalized application for identifying potential winning candidates in future social-media fueled political elections.

The authors presented a simple yet effective model for identifying influential spreaders in the Twitter political sphere. The application of the authors’ approach yielded the conclusion that online “coreness” score has significant influence to the final offline electoral results. This presents great opportunities for applying the novel methodology in the upcoming Malaysian General Election in 2018. The discovery presented here can be used for understanding how different players of political parties engage themselves in the election game in Twitter. The approach can also be adopted as a factor of influence for offline electoral activities. The conception of a quantitative approach in electoral results greatly influenced by social media means that comparative studies could be made in future elections.

Existing works related to general elections of various nations have either bypassed or ignored the subtle links between online and offline influential propagations. The modeling of influence from social media using a longitudinal and multilayered approach is also rarely studied. This simple yet effective method provides a new perspective of practice for understanding how different players behave and mutually shape each other over time in the election game.

The purpose of this paper is to develop a framework on international corporate social responsibility (ICSR). This ICSR framework would help portray the nature and process of internationalization of CSR activities of a firm. Further, this review paper presents a typology on the internationalization of corporate social responsibility (CSR) activities of a firm.

In this conceptual review paper, the author based upon inputs from a diverse set of the extant literature on international business strategy, resource-based view, stakeholder theory, strategic planning and implementation applied logical argumentation incrementally and sequentially to develop the ICSR framework and subsequently ICSR typology (consisting of archetypes).

This conceptual review paper offers a novel and rich theoretical perspective on an integrated framework on ICSR. This expands the extant theoretical knowledge boundaries on internationalization of CSR. Further, the proposed ICSR framework not only provides insight into the process of internationalization of CSR but also on typology regarding the nature of internationalization of CSR activities of a firm.

There are two major theoretical contributions. First, this is one of the first integrated frameworks on ICSR that encompasses perspectives from diverse literature domains such as business environment, stakeholder theory, resource-based view, bounded rationality, bounded reliability, strategy planning and strategy execution. The second major theoretical contribution is towards categorization of firm international CSR activities based on CSR characteristics and mechanisms of deployment. The author prescribed four typologies for ICSR based upon variances in CSR perspective and CSR management. This ICSR categorization or archetypes is also a theoretical contribution.

The International Corporate Social Responsibility (ICSR framework developed would help both strategy and CSR managers to design ICSR programs and CSR activities of a firm based on a firms’ transferable resources and capabilities, replicable organizational process and activities, strategic focus and expected organizational benefits.

This is the first scholarly work on developing an integrated ICSR framework and ICSR typology (read archetypes). In this review paper, a holistic but comprehensive theoretical perspective on strategy and typology of ICSR has been provided. CSR and strategy managers for the first time would have a tool to design and manage firm international CSR initiatives in an effective and efficient manner.

The purpose of this paper is to identify the influence of the frequency of word exposure on online news based on the availability heuristic concept. So that this is different from most churn prediction studies that focus on subscriber data.

This study examined the churn prediction through words presented the previous studies and additionally identified words what churn generate using data mining technology in combination with logistic regression, decision tree graphing, neural network models, and a partial least square (PLS) model.

This study found prediction rates similar to those delivered by subscriber data-based analyses. In addition, because previous studies do not clearly suggest the effects of the factors, this study uses decision tree graphing and PLS modeling to identify which words deliver positive or negative influences.

These findings imply an expansion of churn prediction, advertising effect, and various psychological studies. It also proposes concrete ideas to advance the competitive advantage of companies, which not only helps corporate development, but also improves industry-wide efficiency.

Purpose – The purpose of the research reported in this article is to understand how refugees learn to engage with a complex, multimodal information landscape and how their information literacy practice may be constructed to enable them to connect and be included in their new information landscape. Design/methodology/approach – The study is framed through practice and socio‐cultural theories. A qualitative research design is employed including semi‐structured face‐to‐face interviews and focus groups which are thematically analysed through an information practice lens. Findings – Refugees encounter complex and challenging information landscapes that present barriers to their full participation in their new communities. Social inclusion becomes possible where information is provided via sharing through trusted mediators who assist with navigating the information landscape and information mapping, and through visual and social sources. Research limitations/implications – The study is local and situated and therefore not empirically generalizable. It does however provide rich, deep description and explanation that is instructive beyond the specific research site and contributes to theory building. Practical implications – The study highlights the role, and importance, of social and visual information sources and the key role of service providers as mediators and navigators. Governments, funders and service providers can use these findings to inform their service provision. Originality/value – This is an original research paper in which the results provide practical advice for those working with refugees and which also extends theories of information literacy practice as an information practice.

The purpose of this paper is to design a supply chain database schema for Cassandra to store real-time data generated by Radio Frequency IDentification technology in a traceability system.

The real-time data generated in such traceability systems are of high frequency and volume, making it difficult to handle by traditional relational database technologies. To overcome this difficulty, a NoSQL database repository based on Casandra is proposed. The efficacy of the proposed schema is compared with two such databases, document-based MongoDB and column family-based Cassandra, which are suitable for storing traceability data.

The proposed Cassandra-based data repository outperforms the traditional Structured Query Language-based and MongoDB system from the literature in terms of concurrent reading, and works at par with respect to writing and updating of tracing queries.

The proposed schema is able to store the real-time data generated in a supply chain with low latency. To test the performance of the Cassandra-based data repository, a test-bed is designed in the lab and supply chain operations of Indian Public Distribution System are simulated to generate data.