"I’m Eating a Sandwich in Glasgow": Modeling locations with tweets

Social media such as Twitter generate large quantities of data about what a person is thinking and doing in a partic- ular location. We leverage this data to build models of locations to improve our understanding of a user’s geographic context. Understanding the user’s geographic context can in turn enable a variety of services that allow us to present information, recommend businesses and services, and place advertisements that are relevant at a hyper-local level. In this paper we create language models of locations using coordinates extracted from geotagged Twitter data. We model locations at varying levels of granularity, from the zip code to the country level. We measure the accuracy of these models by the degree to which we can predict the location of an individual tweet, and further by the accuracy with which we can predict the location of a user. We find that we can meet the performance of the industry standard tool for pre- dicting both the tweet and the user at the country, state and city levels, and far exceed its performance at the hyper-local level, achieving a three- to ten-fold increase in accuracy at the zip code level

Mindfulness and therapeutic relationships: insights from a phenomenological study of occupational therapists' practices

Background A well-established body of literature highlights the importance of the therapeutic relationship when working with children and youth. A growing body of literature points to the potential of mindfulness to enhance the quality of relationships, including the therapeutic relationship. To date, little attention has been paid to this topic within the profession of occupational therapy. Aim The aim of this study was to inquire into paediatric occupational therapists’ experiences of mindfulness in the therapeutic relationship with children and youth.  Methods Heideggerian-informed hermeneutic phenomenology was employed as the methodological approach. Two key Heideggerian concepts of being-with and care served as theoretical underpinnings of the study. Semi-structured interviews were completed with eight North American occupational therapists to elicit their first-hand accounts of mindfulness in the therapeutic relationship with their paediatric clients. Interviews were transcribed verbatim and analyzed using a phenomenological approach. Results Four key themes were identified and include: fostering a safe space, enhancing presence, being authentic, and cultivating acceptance. Conclusions The findings offer insights regarding the potential affordances of mindfulness to support clinicians as they form of therapeutic relationships with children and youth. This study highlights research priorities for future inquiry.&nbsp

From Web 1.0 to Web 2.0 and back - How did your Grandma use to tag?

We consider the applicability of terms extracted from anchortext as a source of Web page descriptions in the form of tags. With a relatively simple and easy-to-use method, we show that anchortext significantly overlaps with tags obtained from the popular tagging portal del.icio.us. Considering the size and diversity of the user community potentially involved in social tagging, this observation is rather surprising. Furthermore, we show by an evaluation using human-created relevance assessments the general suitability of the anchortext tag generation in terms of user-perceived precision values. The awareness of this easy-to-obtain source of tags could trigger the rise of new tagging portals pushed by this automatic bootstrapping process or be applied in already existing portals to increase the number of tags per page by merely looking at the anchortext which exists anyway

Augmenting Social Media Items with Metadata using Related Web Content

The Web has shifted from a read-only medium where most users were solely consumers of information, to an interactive medium where collaborative technologies allow anyone to publish or edit content. In this environment, social media such as social network sites, blogs, wikis, and content-sharing websites have flourished and now masses of users are contributing to the pool of human knowledge that is the Web. This large-scale user participation means that the content-creation capacity of the Web has exploded and there is now wide coverage of news, niche interests and hyperlocal content, all available in real-time. In short, Web 2.0 services have successfully harnessed collective intelligence and a huge and diverse information source has emerged. The downside of social media as an information source is that often the individual items are very short, informal and lacking in metadata. Despite the wealth of information available in online communities, locating objects of interest can still be challenging. The search and navigation of social media could be greatly improved by augmenting the content of social media items with annotations to provide additional context or descriptors. This thesis investigates the potential of using related data from the Web to enrich social media items with metadata and thus make it easier to find or browse information in social media. We provide three methods by which social media items can be augmented with novel metadata, specifically tags, locations and categories. Our approaches make use of existing Web data retrieved from HTML documents, APIs and Linked Data. We describe how Semantic Web technologies can be used to represent social media posts and their metadata in a uniform way and thus allow enhanced search and browsing over online community data integrated from heterogeneous sources

An Empirical Investigation of Networks in the Blogosphere

We seek out to investigate the social networks manifested in weblogs. Our dataset, derived from an initial list of URIs, consists of 3.9M files in XML or RDF format, totaling over 400M statements in RDF. We continue by applying well-known network analysis algorithm to parts of the derived net- work. Our experiments show that links analysis algorithms benefit from input in a common, structured data model.peer-reviewe

Understanding online communities by using semantic web technologies

During the last few years, the Web that we used to know as a read-only medium shifted to a read-write Web, often known as Web 2.0 or the Social Web, in which people interact, share and build content collaboratively within online communities. In order to clearly understand how these online communities are formed, evolve, share and produce content, a first requirement is to gather related data. In this chapter, we give an overview of how Semantic Web technologies can be used to provide a unified layer of representation for Social Web data in an open and machine-readable manner thanks to common models and shared semantics, facilitating data gathering and analysis. Through a comprehensive state of the art review, we describe the various models that can be applied to online communities and give an overview of some of the new possibilities offered by such a layer in terms of data querying and community analysis.The work presented in this chapter has been funded in part by Science Foundation Ireland under Grant No. SFI/08/CE/I1380 (Líon 2). We would also like to acknowledge the winners of the SIOC data competition whose entries were referenced in this chapter, as well as Eyal Oren and Benjamin Heitmann for their work on the SIOC Explorer.Not peer reviewe

An Empirical Investigation of Networks in the Blogosphere Abstract

We seek out to investigate the social networks manifested in weblogs. Our dataset, derived from an initial list of URIs, consists of 3.9M files in XML or RDF format, totalling over 400M statements in RDF. We continue by applying wellknown network analysis algorithm to parts of the derived network. Our experiments show that links analysis algorithms benefit from input in a common, structured data model. 1