Tutorials
Below are the accepted Tutorials. All Tutorials will take place on Monday 21 and Tuesday 22 June (please see individual Tutorials for timings).
Business Intelligence Analytics with the Semantic Brand Score
Characterization, Detection, and Mitigation of Cyberbullying
Interactive Demonstrations and Use of the net.science Cyberinfrastructure for Network Science
The decentralization of Social Media through the blockchain technology
Tracking the Trackers: Ethical measurements of web privacy leakages in-the-wild
Business Intelligence Analytics with the Semantic Brand Score
21 June, 15:00 – 20:00 Central European Summer Time
Leveraging the power of big data represents an opportunity for researchers and managers to reveal patterns and trends in social behaviors and consumer perceptions. This workshop presents the Semantic Brand Score (SBS), a methodology of assessment of brand importance that combines methods and tools of Text Mining and Social Network Analysis (Fronzetti Colladon, 2018). The workshop also describes the functionalities of the Semantic Brand Score BI App, which has been designed to assess brand/semantic importance, analize brand image and mine textual data. Its analytical power extends beyond “brands”, comprising applications to study: commercial brands (e.g. Pepsi vs Coke); products (e.g. pasta vs pizza); personal brands (e.g. name and image of political candidates); set of words representing values (e.g. a company’s core values) or concepts related to societal trends (e.g. words used in media communication that impact consumers’ feeling about the state of the economy). The App generates a wide range of analytics that have been used, for example, to build predictive models to understand tourism trends, select advertising campaign testimonials, and make economic, financial and political forecasts. Gaining a deeper understanding of brand importance and image can change the way we make decisions and manage organizations in the era of big data.
Characterization, Detection, and Mitigation of Cyberbullying
21 June, 10:00 – 14:00 Eastern Daylight Time
Tutorial on current computational approaches for the detection, quantification & mitigation of cyberbullying in online social media.
Interactive Demonstrations and Use of the net.science Cyberinfrastructure for Network Science
22 June, 13:00 – 17:00 Eastern Daylight Time
Cyberinfrastructures and gateways are software systems that are accessible by researchers and students for performing wide-ranging computations on data. While the XSEDE science gateway lists more than 40 gateways, and the Science Gateways Community Institute (SGCI) has roughly 600 gateway entries, none is devoted to network science in general. This situation exists despite the fact that much of built infrastructures (e.g., power, water, communications) are networks, and humans form many types of online and face-to-face (social) networks. The generality of networks makes them useful in engineering, science, social sciences, history, psychology, finance, economics, and mathematics, among other fields. The myriad computations performed on networks make them a prime candidate for general-purpose computational tools.
Through funding from the National Science Foundation (NSF), in late 2019, we began the design and implementation of a network science cyberinfrastructure (CI) called net.science. We are on the verge of its initial release. The proposed ½-day tutorial will introduce the net.science CI to participants and enable them to use it to perform computations on networks. This tutorial can be the start of participants’ use of the system, as it is an open access CI.
The decentralization of Social Media through the blockchain technology
22 June, 09:00 – 13:00 Central European Summer Time
The tutorial will be principally focused on the Steem socioeconomic system and it will cover two parts: an overview of how data could be collected, and the setup of graph analyses. In the first part we will build a minimal crawler for the blocks that are published in the blockchain by exploiting the official Python APIs provided by Steem. In the second part of the tutorial, we will show how these data can be used for a number of analyses, showing a concrete example by building a graph of transactions through efficient large scale graph libraries such as Networkit and iGraph.
Tracking the Trackers: Ethical measurements of web privacy leakages in-the-wild
22 June, 14:00 – 18:00 British Summer Time
First introduced in the mid-nineties as a way of recording client-side state, cookies have proliferated widely on the Web, and have become a fundamental part of the Web ecosystem. However, there is widespread concern that cookies are being abused to track and profile individuals online for commercial, analytical and various other purposes. Consequently, there has been an explosion of research into understanding the prevalence of tracking on the Web, and the resulting leakage of Personally Identifiable Information (PII). In this tutorial, we aim to introduce the audience to state-of-the-art empirical measurement methods and techniques that are being used to understand and quantify web tracking in-the-wild. We will cover ethics issues, privacy legislation from around the world and provide a technical background to state of the art tracking techniques before giving a hands-on introduction to empirical measurement methods being used in the field.