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.

Event extraction using behaviors of sentiment signals and burst structure in social media

Significant world events often cause the behavioral convergence of the expression of shared sentiment. This paper examines the use of the blogosphere as a framework to study user psychological behaviors, using their sentiment responses as a form of ‘sensor’ to infer real-world events of importance automatically. We formulate a novel temporal sentiment index function using quantitative measure of the valence value of bearing words in blog posts in which the set of affective bearing words is inspired from psychological research in emotion structure. The annual local minimum and maximum of the proposed sentiment signal function are utilized to extract significant events of the year and corresponding blog posts are further analyzed using topic modeling tools to understand their content. The paper then examines the correlation of topics discovered in relation to world news events reported by the mainstream news service provider, Cable News Network, and by using the Google search engine. Next, aiming at understanding sentiment at a finer granularity over time, we propose a stochastic burst detection model, extended from the work of Kleinberg, to work incrementally with stream data. The proposed model is then used to extract sentimental bursts occurring within a specific mood label (for example, a burst of observing ‘shocked’). The blog posts at those time indices are analyzed to extract topics, and these are compared to real-world news events. Our comprehensive set of experiments conducted on a large-scale set of 12 million posts from Livejournal shows that the proposed sentiment index function coincides well with significant world events while bursts in sentiment allow us to locate finer-grain external world events.

Identity and self-presentation : from a representational to a performative lens in studying social media engagement in organisations

Social media make fast inroads into organisations. This raises issues regarding self-presentation and locating experts in these new emerging communication spaces, as the basis for effective social media-enabled knowledge work. However, research on self-presentation and identity in organisational social media is only just emerging and has been founded on broader understandings from studies of public social media. In this literature study we demonstrate that the existing body of research on identity in social media is dominated by a ‘representational lens’. Based on an analysis of the historic foundations of this stream of research, we will expose limitations of this lens in capturing contemporary engagement in online spaces and advocate for a ‘performative lens’ in studying identity work in organisations. We contribute a detailed exposition of the evolution of identity studies in the context of public social media, and we offer an alternative lens for studying the topic in organisational contexts.

Potentials of social media for tacit knowledge sharing amongst physicians : preliminary findings

Tacit knowledge sharing amongst physicians, such as the sharing of clinical experiences, skills, or know-how, or know-whom, is known to have a significant impact on the quality of medical diagnosis and decisions. This paper posits that social media can provide new opportunities for tacit knowledge sharing amongst physicians, and demonstrates this by presenting findings from a review of relevant literature and a survey conducted with physicians. Semi-structured interviews were conducted with ten physicians from around the world who were active users of social media. Initial thematic analysis revealed eight themes as potential contributions of social web tools to facilitate tacit knowledge flow amongst physicians. The emergent themes are defined, linked to the literature, and supported by instances of interview transcripts. Findings presented here are preliminary, and final results will be reported after accomplishing all phases of data collection and analysis.

Understanding the role of social media monitoring in generating external intelligence

Social media data are becoming increasingly critical for businesses to capture, analyse, and utilise in a timely manner. However, the unstructured and distributed nature and volume of this information makes the task of extracting useful and practical information challenging. Given the dynamic evolution of social media and social media monitoring, our current understanding of how social media monitoring can help organisations to create business value is inadequate. As a result, there is a need to study how organisations can (a) extract and analyse social media data related to their business (Sensing), and (b) utilise external intelligence gained from social media monitoring for specific business initiatives (Seizing). This study uses a qualitative approach with a multiple embedded case study design to understand the phenomenon of social media monitoring and its outcome for organisations. Anticipated contributions are presented.

Social media in the classroom : a simple yet complex hybrid environment for students

This article reports on part of the author’s PhD action research study. It examines the complexity of features that social media and Web 2.0 offer when combined with face-to-face teaching and learning. Action research was used to help redesign the learning programs of thirteen Middle Years classes over an eighteen month period. These learning programs took advantage of the unique communicative methods offered by social media and provided spaces such as blogs, groups and discussion forums. Students developed their own identity when working online, made online friends, left comments for peers and uploaded content which included publishing, peer reviewing and self assessment. The research highlighted the simplicity in the creation and exchange of user-generated content and interaction while identifying a complex depth behind such interaction. Designing learning programs using social media enabled the students to be active and valued participants in the learning process and a ‘hybrid’ learning environment

Designing social media into university learning : technology of collaboration or collaboration for technology?

Using the example of an undergraduate unit of study that is taught both on-campus and externally, but uses Internet-based learning in both cases, we explore how social media might be used effectively in higher education. We place into question the assumption that such technologies necessarily engage students in constructivist learning; we argue that the affordances of social media must be complemented by social affordances, designed into the learning experience, which thereby generate the necessary connection between students’ motivations to study and their motivations to exploit social media. We demonstrate, via the example given, how assessment structures and strategies are the most effective focus when attempting to create the pedagogical affordances that might lead to collaborative learning.