A study into how Australian banks use social media

Social Media is a term commonly used to describe a group of individual web based services that have grown beyond the provisioning of the capability to connect, network or blog. The popular social networking services have evolved into a ‘platform’ by incorporating a multitude of functionalities through an array of applications to attract millions of users. This has created a favourable environment for businesses to exploit the benefit of having access to millions of social media users by using it as a business support tool. Studies indicate that social media services are being used by businesses for engaging with the general public, enhancing customer interaction, and for crisis communications. Whilst there are many businesses who have adopted social media, others have either rejected the idea or are still unsure about how to proceed. This paper analyses the functionality of selected social media services in order to explore how Australian banks use such services strategically. It reports findings from a longitudinal study of Australian bank use of four popular social media services: Facebook, MySpace, Twitter, and YouTube.

The role of entrepreneurial marketing in social media

Social media are increasingly emerging as a source of competitive advantage, as a means of reaching and engaging consumers, and as a source of consumer insight. This paper identifies challenges associated with the implementation of social media as perceived by senior marketers. Using a qualitative thematic analysis methodology, we identify differences between entrepreneurial and nonentrepreneurial organisations in social media implementation. It is proposed that entrepreneurial marketing may provide theoretical guidelines for implementation of social media. The paper concludes with research propositions that will test the effectiveness of entrepreneurial marketing in overcoming the implementation challenges of social media.

Can qualitative content analysis be adapted for use by social informaticians to study social media discourse? A position paper

IS research on social media (e.g. Facebook, Twitter, blogs) has so far used user surveys or quantitative content analysis (QuantCA) research methods almost exclusively. There is considerable potential for social informatics research to use qualitative content analysis (QualCA) to explore social media discourse and its appropriation by people “in situ”. This paper presents the position that QualCA offers researchers the flexibility to identify emergent research questions and units of analysis which they may not have preconceived. This is likely to be important for IS research because of the infancy and evolving nature of social media discourse. The paper puts forward suggestions on how the QualCA research method can be adapted for this type of research.

Blogs bother me : social media, journalism and the curriculum

This paper grew out of the authors’ interest in updating the journalism curriculum at AUT (Aukland University of Technology) to better reflect the impact of online media, including social media, on the work of journalists. The challenge for journalism educators is to remain relevant in rapidly changing news and education environments. Our study suggests that while the vast majority of students have some engagement with social media, particularly social networking, and are aware that it can be a powerful tool for journalists, they are still not entirely comfortable with its techniques and they are not experimenting with social media as a production platform as much as we first thought. In short, it appears that they do not have command of professional fluency with social media tools. In response to these findings we have begun to introduce some social media tools and processes directly into the units we teach, in particular: digital story-telling techniques; the use of Twitter and location-based applications; encouraging the ethical use of Facebook etc. for sourcing stories and talent for interviews; podcasting, soundslides and video for the Web, Dreamweaver, InDesign and PHP-based content management systems. We do not see the work to date as the end-point of the changes that we know are necessary, but we are acutely aware of the limitations (structural, institutional and financial) that suggest we should continue with this small-steps approach for the foreseeable future.

From Masterchef to the Arab spring via Wikileaks : social media and political change

This comparison between Bahrain and Australia shows how the main impact of social and mobile media has been in the form of facilitators of rapid political mobilization, as well as tools for everyday socializing and entertainment. Social media are both contributors to, and symptomatic of, a blurring of the boundaries between politics and entertainment, and public and private spheres, whether their users are in Australia or Bahrain, but they are not in themselves the makers of material sites of democracy or even agency.

A framework for elearning with social media using DRM

This paper provides a proposal for personal e-learning system (PELS) architecture in the context of social network environment. The main objective of PELS is to develop individual skills on a specific subject and share resources with peers. Our system architecture defines organization and management of personal learning environment that aids in creating, verifying and sharing learning artifacts and making money at the same time. We also focus on in our research one of the most interesting arenas in digital content or document management called Digital Right Management (DRAM) and its application to eLearning.

Nonnegative shared subspace learning and its application to social media retrieval

Although tagging has become increasingly popular in online image and video sharing systems, tags are known to be noisy, ambiguous, incomplete and subjective. These factors can seriously affect the precision of a social tag-based web retrieval system. Therefore improving the precision performance of these social tag-based web retrieval systems has become an increasingly important research topic. To this end, we propose a shared subspace learning framework to leverage a secondary source to improve retrieval performance from a primary dataset. This is achieved by learning a shared subspace between the two sources under a joint Nonnegative Matrix Factorization in which the level of subspace sharing can be explicitly controlled. We derive an efficient algorithm for learning the factorization, analyze its complexity, and provide proof of convergence. We validate the framework on image and video retrieval tasks in which tags from the LabelMe dataset are used to improve image retrieval performance from a Flickr dataset and video retrieval performance from a YouTube dataset. This has implications for how to exploit and transfer knowledge from readily available auxiliary tagging resources to improve another social web retrieval system. Our shared subspace learning framework is applicable to a range of problems where one needs to exploit the strengths existing among multiple and heterogeneous datasets.

Prediction of age, sentiment, and connectivity from social media text

Social media corpora, including the textual output of blogs, forums, and messaging applications, provide fertile ground for linguistic analysis material diverse in topic and style, and at Web scale. We investigate manifest properties of textual messages, including latent topics, psycholinguistic features, and author mood, of a large corpus of blog posts, to analyze the impact of age, emotion, and social connectivity. These properties are found to be significantly different across the examined cohorts, which suggest discriminative features for a number of useful classification tasks. We build binary classifiers for old versus young bloggers, social versus solo bloggers, and happy versus sad posts with high performance. Analysis of discriminative features shows that age turns upon choice of topic, whereas sentiment orientation is evidenced by linguistic style. Good prediction is achieved for social connectivity using topic and linguistic features, leaving tagged mood a modest role in all classifications.