Measuring Network Structure Metrics as a Proxy for Socio-political Activity in Social Media

Social surveys have been used by researchers and policy makers as an essential tool for understanding social and political activities in society. Social media has introduced a new way of capturing data from large numbers of people. Unlike surveys, social media deliver data more rapidly and cheaply. In this paper, we aim to rapidly identify socio-political activity in South Africa using proxy data from social media. We measure and analyse scalar properties of a network created by user interactions on Twitter. Our experimental results show that network diameter and reciprocity have statistical significance in determining socio-political activity

Data Portraits and Intermediary Topics: Encouraging Exploration of Politically Diverse Profiles

In micro-blogging platforms, people connect and interact with others. However, due to cognitive biases, they tend to interact with like-minded people and read agreeable information only. Many efforts to make people connect with those who think differently have not worked well. In this paper, we hypothesize, first, that previous approaches have not worked because they have been direct -- they have tried to explicitly connect people with those having opposing views on sensitive issues. Second, that neither recommendation or presentation of information by themselves are enough to encourage behavioral change. We propose a platform that mixes a recommender algorithm and a visualization-based user interface to explore recommendations. It recommends politically diverse profiles in terms of distance of latent topics, and displays those recommendations in a visual representation of each user's personal content. We performed an "in the wild" evaluation of this platform, and found that people explored more recommendations when using a biased algorithm instead of ours. In line with our hypothesis, we also found that the mixture of our recommender algorithm and our user interface, allowed politically interested users to exhibit an unbiased exploration of the recommended profiles. Finally, our results contribute insights in two aspects: first, which individual differences are important when designing platforms aimed at behavioral change; and second, which algorithms and user interfaces should be mixed to help users avoid cognitive mechanisms that lead to biased behavior.Comment: 12 pages, 7 figures. To be presented at ACM Intelligent User Interfaces 201

Social Media Fingerprints of Unemployment

Anexo: Supporting Information. This file contains Figures A-I, Tables A-F and Sections A-I.Recent widespread adoption of electronic and pervasive technologies has enabled the study of human behavior at an unprecedented level, uncovering universal patterns underlying human activity, mobility, and interpersonal communication. In the present work, we investigate whether deviations from these universal patterns may reveal information about the socio-economical status of geographical regions. We quantify the extent to which deviations in diurnal rhythm, mobility patterns, and communication styles across regions relate to their unemployment incidence. For this we examine a country-scale publicly articulated social media dataset, where we quantify individual behavioral features from over 19 million geo-located messages distributed among more than 340 different Spanish economic regions, inferred by computing communities of cohesive mobility fluxes. We find that regions exhibiting more diverse mobility fluxes, earlier diurnal rhythms, and more correct grammatical styles display lower unemployment rates. As a result, we provide a simple model able to produce accurate, easily interpretable reconstruction of regional unemployment incidence from their social-media digital fingerprints alone. Our results show that cost-effective economical indicators can be built based on publicly-available social media datasets.Partial funding came from the Spanish Ministry of Economy and Competitiveness through grant FIS2013-47532-C3-3-P, the Australian Government, and the Australian Research Council. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Impact Investing: a primer for family offices

The goal of this report is to help family offices ask the right questions as they contemplate their path into impact investing. It is important to recognize that impact investing may not suit all investors. There will be family offices which conclude impact investing is not appropriate at this stage for them. While we are passionate about the potential of impact investing, we acknowledge the best future for the sector is where each investor can make informed choices about their own best interest. Each investor and investment institution needs to evaluate if impact investing fits with its needs, interests and unique context. It is with that in mind that we offer this report as a resource and tool that family offices can use to begin the conversations internally, to craft and design their own engagement strategy on impact investing with family members, advisers and potential investees, as well as to ensure that not only is their wealth growing in value, but also that their wealth can reflect their values

Citizens and Institutions as Information Prosumers. The Case Study of Italian Municipalities on Twitter

The aim of this paper is to address changes in public communication following the advent of Internet social networking tools and the emerging web 2.0 technologies which are providing new ways of sharing information and knowledge. In particular public administrations are called upon to reinvent the governance of public affairs and to update the means for interacting with their communities. The paper develops an analysis of the distribution, diffusion and performance of the official profiles on Twitter adopted by the Italian municipalities (comuni) up to November 2013. It aims to identify the patterns of spatial distribution and the drivers of the diffusion of Twitter profiles; the performance of the profiles through an aggregated index, called the Twitter performance index (Twiperindex), which evaluates the profiles' activity with reference to the gravitational areas of the municipalities in order to enable comparisons of the activity of municipalities with different demographic sizes and functional roles. The results show that only a small portion of innovative municipalities have adopted Twitter to enhance e-participation and e-governance and that the drivers of the diffusion seem to be related either to past experiences and existing conditions (i.e. civic networks, digital infrastructures) developed over time or to strong local community awareness. The better performances are achieved mainly by small and medium-sized municipalities. Of course, the phenomenon is very new and fluid, therefore this analysis should be considered as a first step in ongoing research which aims to grasp the dynamics of these new means of public communication