Modeling Temporal Evidence from External Collections

Newsworthy events are broadcast through multiple mediums and prompt the crowds to produce comments on social media. In this paper, we propose to leverage on this behavioral dynamics to estimate the most relevant time periods for an event (i.e., query). Recent advances have shown how to improve the estimation of the temporal relevance of such topics. In this approach, we build on two major novelties. First, we mine temporal evidences from hundreds of external sources into topic-based external collections to improve the robustness of the detection of relevant time periods. Second, we propose a formal retrieval model that generalizes the use of the temporal dimension across different aspects of the retrieval process. In particular, we show that temporal evidence of external collections can be used to (i) infer a topic's temporal relevance, (ii) select the query expansion terms, and (iii) re-rank the final results for improved precision. Experiments with TREC Microblog collections show that the proposed time-aware retrieval model makes an effective and extensive use of the temporal dimension to improve search results over the most recent temporal models. Interestingly, we observe a strong correlation between precision and the temporal distribution of retrieved and relevant documents.Comment: To appear in WSDM 201

The Early Bird Catches The Term: Combining Twitter and News Data For Event Detection and Situational Awareness

Twitter updates now represent an enormous stream of information originating from a wide variety of formal and informal sources, much of which is relevant to real-world events. In this paper we adapt existing bio-surveillance algorithms to detect localised spikes in Twitter activity corresponding to real events with a high level of confidence. We then develop a methodology to automatically summarise these events, both by providing the tweets which fully describe the event and by linking to highly relevant news articles. We apply our methods to outbreaks of illness and events strongly affecting sentiment. In both case studies we are able to detect events verifiable by third party sources and produce high quality summaries

CHORUS Deliverable 3.4: Vision Document

The goal of the CHORUS Vision Document is to create a high level vision on audio-visual search engines in order to give guidance to the future R&D work in this area and to highlight trends and challenges in this domain. The vision of CHORUS is strongly connected to the CHORUS Roadmap Document (D2.3). A concise document integrating the outcomes of the two deliverables will be prepared for the end of the project (NEM Summit)

Supporting the Virtual Community: Social Bookmarking as a user- based Classification Scheme in a Knowledge Library

Knowledge libraries hold the promise of widespread access to information available anywhere, anytime, freeing patrons from the geographical and temporal boundaries that currently exist. The classification of materials and subsequent searching of knowledge library content is an overall problem with many complex parts. Relevant classification is important for optimal information retrieval. This is especially important for the virtual communities that exist with extended organizations. Rooted in the virtual community and digital library literature, this paper develops a theory for improving the information classification and retrieval process of knowledge libraries that support virtual communities by applying social bookmarking techniques

Confounds and Consequences in Geotagged Twitter Data

Twitter is often used in quantitative studies that identify geographically-preferred topics, writing styles, and entities. These studies rely on either GPS coordinates attached to individual messages, or on the user-supplied location field in each profile. In this paper, we compare these data acquisition techniques and quantify the biases that they introduce; we also measure their effects on linguistic analysis and text-based geolocation. GPS-tagging and self-reported locations yield measurably different corpora, and these linguistic differences are partially attributable to differences in dataset composition by age and gender. Using a latent variable model to induce age and gender, we show how these demographic variables interact with geography to affect language use. We also show that the accuracy of text-based geolocation varies with population demographics, giving the best results for men above the age of 40.Comment: final version for EMNLP 201

Report of the Stanford Linked Data Workshop

The Stanford University Libraries and Academic Information Resources (SULAIR) with the Council on Library and Information Resources (CLIR) conducted at week-long workshop on the prospects for a large scale, multi-national, multi-institutional prototype of a Linked Data environment for discovery of and navigation among the rapidly, chaotically expanding array of academic information resources. As preparation for the workshop, CLIR sponsored a survey by Jerry Persons, Chief Information Architect emeritus of SULAIR that was published originally for workshop participants as background to the workshop and is now publicly available. The original intention of the workshop was to devise a plan for such a prototype. However, such was the diversity of knowledge, experience, and views of the potential of Linked Data approaches that the workshop participants turned to two more fundamental goals: building common understanding and enthusiasm on the one hand and identifying opportunities and challenges to be confronted in the preparation of the intended prototype and its operation on the other. In pursuit of those objectives, the workshop participants produced:1. a value statement addressing the question of why a Linked Data approach is worth prototyping;2. a manifesto for Linked Libraries (and Museums and Archives and …);3. an outline of the phases in a life cycle of Linked Data approaches;4. a prioritized list of known issues in generating, harvesting & using Linked Data;5. a workflow with notes for converting library bibliographic records and other academic metadata to URIs;6. examples of potential “killer apps” using Linked Data: and7. a list of next steps and potential projects.This report includes a summary of the workshop agenda, a chart showing the use of Linked Data in cultural heritage venues, and short biographies and statements from each of the participants