Reading and Responding to the Digital Footprints of Mobile Visitors

2016 ◽  
pp. 299-320
Author(s):  
Ben Bedwell
Keyword(s):  
Digital Footprints

scholarly journals Methodology and Models for Individuals’ Creditworthiness Management Using Digital Footprint Data and Machine Learning Methods

Mathematics ◽  
2021 ◽  
Vol 9 (15) ◽  
pp. 1820
Author(s):  
Ekaterina V. Orlova
Keyword(s):  
Interest Rates ◽  
Additional Data ◽  
Risk Level ◽  
Gradient Boosting ◽  
Cluster Number ◽  
New Approach ◽  
Credit Risks ◽  
Stochastic Gradient Boosting ◽  
The Stability ◽  
Digital Footprints

This research deals with the challenge of reducing banks’ credit risks associated with the insolvency of borrowing individuals. To solve this challenge, we propose a new approach, methodology and models for assessing individual creditworthiness, with additional data about borrowers’ digital footprints to implement comprehensive analysis and prediction of a borrower’s credit profile. We suggest a model for borrowers’ clustering based on the method of hierarchical clustering and the k-means method, which groups actual borrowers having similar creditworthiness and similar credit risks into homogeneous clusters. We also design the model for borrowers’ classification based on the stochastic gradient boosting (SGB) method, which reliably determines the cluster number and therefore the risk level for a new borrower. The developed models are the basis for decision making regarding the decision about lending value, interest rates and lending terms for each risk-homogeneous borrower’s group. The modified version of the methodology for assessing individual creditworthiness is presented, which is to reduce the credit risks and to increase the stability and profitability of financial organizations.

Extracting social and community intelligence from digital footprints

2012 ◽  
Vol 5 (1) ◽  
pp. 1-2 ◽  
Author(s):  
Bin Guo ◽  
Daqing Zhang ◽  
Zhiwen Yu ◽  
Francesco Calabrese
Keyword(s):  
Social And Community Intelligence ◽  
Digital Footprints ◽  
Community Intelligence

Big Data Analysis with No Digital Footprints Available: Evidence from Cyber-Telecom Fraud

2020 ◽  
Author(s):  
Laura Xiaolei Liu ◽  
Yufei Liu ◽  
Xinghua Ruan ◽  
Yu Zhang
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Big Data Analysis ◽  
Digital Footprints

Digital footprints in the university space

2021 ◽  
Vol 4 (2) ◽  
pp. 52-72
Author(s):  
Timur Khusyainov
Keyword(s):  
Personal Data ◽  
Educational Environment ◽  
Educational Process ◽  
Global Network ◽  
Ethical Standards ◽  
Digital Footprint ◽  
Digital Environments ◽  
The Moment ◽  
The University ◽  
Digital Footprints

This work considers the use of digital traces in the educational environment and the specifics of their collection and analysis at the university. One way or another, all participants in the educational process, as well as those who can potentially become them, for example, applicants, leave digital traces in the digital environments of the university and the Global Network in general, and these traces can be analyzed. At the same time, even the university itself as an organization leaves a certain digital footprint on the Internet. At the moment, most researchers are very optimistic, contemplating on what positive changes can be brought by the analysis of digital traces of applicants, students and teachers for the development of the university itself, the educa-tional process, and the formation of individual learning paths. In contrast to this, the author identifies a number of possible prospects for the analysis of Big Data and the use of Artificial Intelligence for education at the university of the future. Attention is focused on how this can affect the safety of the environment and conflict with ethical standards. Participants in the educational process, falling under the analysis of their digital traces, can both suffer because of them, even if their activities have not been in any way connected with the university, and begin to hide their true digital identity, creating «false» digital traces and becoming anon-ymous. The author assumes that an increase in such control covering actions, thoughts and emotions naturally results in the emergence of the concept of a «Dark» University, which distances itself as much as possible from such methods of analyzing personal data.

Facebook Digital Traces for Survey Research: Assessing the Efficiency and Effectiveness of a Facebook Ad–Based Procedure for Recruiting Online Survey Respondents in Niche and Difficult-to-Reach Populations

2018 ◽  
Vol 38 (4) ◽  
pp. 462-476
Author(s):  
Laura Iannelli ◽  
Fabio Giglietto ◽  
Luca Rossi ◽  
Elisabetta Zurovac
Keyword(s):  
Online Survey ◽  
Computer Assisted ◽  
Previous Survey ◽  
Innovative Method ◽  
Entry Points ◽  
Efficiency And Effectiveness ◽  
Recent Developments ◽  
Proper Comparison ◽  
Facebook Advertising ◽  
Digital Footprints

Survey-based studies are increasingly experimenting with strategies that employ digital footprints left by users on social media as entry points for recruiting participants and complementary data sources. In this perspective, the Facebook advertising platform provides unique opportunities and challenges through its marketing tools that target advertisements based on users’ demographics, behaviors, and interests. This article presents a procedure that employed the most recent developments in Facebook marketing tools to evaluate the efficiency and effectiveness of an innovative method for recruiting niche and traditionally hard-to-reach respondents. Although the multiple innovations introduced in the method hinder a proper comparison with previous studies, the survey provides evidence concerning the efficacy of the procedure and offers scholars a set of implementations to design future comparable Facebook ad–based surveys. Challenges, opportunities, and results for effectiveness are discussed in light of a previous survey on Italian adults carried out with a panel-based computer-assisted web interviewing method.

scholarly journals VIRTUAL SPACE AS A SOURCE OF PRIMARY SOCIAL INFORMATION

2020 ◽  
Keyword(s):  
Social Life ◽  
Quantitative Methods ◽  
Rapid Development ◽  
Virtual Space ◽  
Sociological Research ◽  
Demographic Model ◽  
Sociological Approach ◽  
Qualitative Approaches ◽  
Sociological Method ◽  
Digital Footprints

The rapid development of the Internet has had an unprecedented impact on the improvement of the sociological method. At the turn of the millennium, this has led to the search for a new methodology and a gradual loss of interest to use of quantitative methods, which was perceived by specialists as a "crisis of empirical sociology". In the last decade, it turned out that almost all social processes of any level find their reflection in the virtual space, leave and accumulate so-called "digital footprints", which opens to researchers the widest perspectives for study of social reality. This article considers the features of digital primary information and generalized approaches to its use in terms of quantitative methodology. The author emphasizes that the classical sociological methods, which are based on mathematical statistics, are suitable for the analysis of digital reality and getting adequate research results. At the same time, as noted by most authors, who have studied this subject, there are perspectives for improving traditional sociological methods through: 1) a combination of representativeness of quantitative and depth of qualitative approaches to information analysis; 2) in-depth collection of paradata; 3) opportunities to study hard-to-reach social groups; 4) opportunities to fully implement the "principle of freedom from evaluation" due to the "non-reactivity" of digital data; 5) the ordering of digital footprints in space and time by clearly fixing the hosting. The post-demographic model of the social actor opens new ways to build samples of quantitative sociological research, which may be representative in terms of the classical sociological approach. The examples of research from this article show that the classical sociological method easily to adapt for the new digital reality and can be the basis for sociological consulting, development of social technologies in various spheres of social life.

scholarly journals Online Surveillance in a Swedish Context

2020 ◽  
Vol 41 (2) ◽  
pp. 179-193
Author(s):  
Coppélie Cocq ◽  
Stefan Gelfgren ◽  
Lars Samuelsson ◽  
Jesper Enbom
Keyword(s):  
Qualitative Methods ◽  
Digital Media ◽  
Surveillance Culture ◽  
Humanistic Approach ◽  
Societal Level ◽  
Technical Solutions ◽  
Digital Footprints

AbstractUsers of digital media leave traces that corporations and authorities can harvest, systematise, and analyse; on the societal level, an overall result is the emergence of a surveillance culture. In this study, we examine how people handle the dilemma of leaving digital footprints: what they say they do to protect their privacy and what could legitimise the collection and storing of their data. Through a survey of almost 1,000 students at Umeå University in Sweden, we find that most respondents know that their data are used and choose to adjust their own behaviour rather than adopting technical solutions. In order to understand contemporary forms of surveillance, we call for a humanistic approach – an approach where hermeneutic and qualitative methods are central.

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