Social Media for Cities, Counties and Communities

Social media (i.e., Twitter, Facebook, Flickr, YouTube) and other tools and services with user- generated content have made a staggering amount of information (and misinformation) available. Some government officials seek to leverage these resources to improve services and communication with citizens, especially during crises and emergencies. Yet, the sheer volume of social data streams generates substantial noise that must be filtered. Potential exists to rapidly identify issues of concern for emergency management by detecting meaningful patterns or trends in the stream of messages and information flow. Similarly, monitoring these patterns and themes over time could provide officials with insights into the perceptions and mood of the community that cannot be collected through traditional methods (e.g., phone or mail surveys) due to their substantive costs, especially in light of reduced and shrinking budgets of governments at all levels. We conducted a pilot study in 2010 with government officials in Arlington, Virginia (and to a lesser extent representatives of groups from Alexandria and Fairfax, Virginia) with a view to contributing to a general understanding of the use of social media by government officials as well as community organizations, businesses and the public. We were especially interested in gaining greater insight into social media use in crisis situations (whether severe or fairly routine crises, such as traffic or weather disruptions)

Image-based Social Sensing: Combining AI and the Crowd to Mine Policy-Adherence Indicators from Twitter

Social Media provides a trove of information that, if aggregated and analysed appropriately can provide important statistical indicators to policy makers. In some situations these indicators are not available through other mechanisms. For example, given the ongoing COVID-19 outbreak, it is essential for governments to have access to reliable data on policy-adherence with regards to mask wearing, social distancing, and other hard-to-measure quantities. In this paper we investigate whether it is possible to obtain such data by aggregating information from images posted to social media. The paper presents VisualCit, a pipeline for image-based social sensing combining recent advances in image recognition technology with geocoding and crowdsourcing techniques. Our aim is to discover in which countries, and to what extent, people are following COVID-19 related policy directives. We compared the results with the indicators produced within the CovidDataHub behavior tracker initiative. Preliminary results shows that social media images can produce reliable indicators for policy makers.Comment: 10 pages, 9 figures, to be published in Proceedings of ICSE Software Engineering in Society, May 202

Identification and Comparison of Gray Literature in Two Polar Libraries: Australian Antarctic Division and Scott Polar Research Institute

Gray literature collections were investigated and compared at the libraries of the Australian Antarctic Division (AAD) and the Scott Polar Research Institute (SPRI) in order to improve accessibility. These collections are important to Arctic and Antarctic researchers, but are problematic because they are not well documented, often have limited access, and are arranged by subject using a classification system specific to polar libraries. Tangible results of the project include estimates of the number of gray literature items in the polar subject categories for the two libraries, along with a template of a user’s finding aid to these collections. In addition, 172 sources from four Antarctic expeditions in the early part of the 20th century were selected as a representative sample; 64 from AAD and 108 from SPRI. While small, the sample was a focused topic with enough variety of materials to provide good examples for accessibility issues. Inquiries are continually received at AAD and SPRI for information related to these four expeditions, so improved access will be beneficial for both researchers and the two institutions. Making the material more available is also very timely, anticipating renewed interest from the public with the approaching centennial celebrations of two of the expeditions coming up in 2010 and 2011. Despite the similar subject nature of the collections, only ten items were duplicated in the two libraries. Solutions for improving access, such as linking the gray literature collections to broader initiatives are addressed in more detail in the final report. Providing the references in a metadata format to include in an online catalog or linked to a website will increase visibility and use of the materials. Suggestions for improving the arrangement of the materials and reducing duplication within the collections are also discussed in the final report available on my blog. http://www.consortiumlibrary.org/blogs/dcarle/sabbatical/Summary / Project Background / Project Methodology Part I / Results Part I / Project Methodology and Results Part II / Discussion and Recommendations / Additional Activities / Additional Accomplishments / Additional Professional Activities / Project Goals Not Completed/ Benefitsof Sabbatical / Conclusion and Acknowledgement

Collaborative trails in e-learning environments

This deliverable focuses on collaboration within groups of learners, and hence collaborative trails. We begin by reviewing the theoretical background to collaborative learning and looking at the kinds of support that computers can give to groups of learners working collaboratively, and then look more deeply at some of the issues in designing environments to support collaborative learning trails and at tools and techniques, including collaborative filtering, that can be used for analysing collaborative trails. We then review the state-of-the-art in supporting collaborative learning in three different areas – experimental academic systems, systems using mobile technology (which are also generally academic), and commercially available systems. The final part of the deliverable presents three scenarios that show where technology that supports groups working collaboratively and producing collaborative trails may be heading in the near future

A machine-learning approach to Detect users' suspicious behaviour through the Facebook wall

Facebook represents the current de-facto choice for social media, changing the nature of social relationships. The increasing amount of personal information that runs through this platform publicly exposes user behaviour and social trends, allowing aggregation of data through conventional intelligence collection techniques such as OSINT (Open Source Intelligence). In this paper, we propose a new method to detect and diagnose variations in overall Facebook user psychology through Open Source Intelligence (OSINT) and machine learning techniques. We are aggregating the spectrum of user sentiments and views by using N-Games charts, which exhibit noticeable variations over time, validated through long term collection. We postulate that the proposed approach can be used by security organisations to understand and evaluate the user psychology, then use the information to predict insider threats or prevent insider attacks.Comment: 8 page

Social media processing in crisis response : an attempt to shift from data to information exploitation.

Information about the ongoing events is of the utmost importance during emergencies. Previous work in crisis informatics found new ways to pull data from unexploited sources, such as social media. But while the volume of information is crucial, the way the information is reported and provided becomes increasingly important as the volume grows. Yet, little has been achieved on information management. This article proposes a way to automatically organize information from social media data up to decision-makers. This organization is enabled by a metamodel \cite{benaben_metamodel_2016} designed to model crucial information in crises. The article is organized as follows. First, the organization of current social media processing systems is presented. Then, the article presents the metamodel used and how it is relevant to organized information in crisis events through the lens of the 6W\u27s \cite{kropczynski_identifying_2018}. Finally, it walks through the implementation of the proposal based on the two previous parts