Assessing strategies for sampling dynamic social networks

Paolo Ceravolo, Francesco Ciclosi, Emanuele Bellini, Ernesto Damiani

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Social Networks represents an invaluable source of information to detect, understand and predict social trends and complex dynamics. Unfortunately, the presence of several constraints in data collections as costs, dimensions, time and so forth, requires the implementation of a sampling strategy able to maximize the information value for the analysis. The paper defines a number of parameters and thresholds defining a new strategy for data sampling in social network and compares samples obtained with different strategies. The test case has been conducted on the social network of the mayors of four Italian metropolitan areas. Results of the assessment reveal that the parameter designed for configuring a strategy impacts on the dimension, the extraction time and the quality of the generated network as expected. The best tradeoff between quality and execution time has been identified and discussed.

Original languageBritish English
Title of host publicationResearch and Innovation Forum 2019 - Technology, Innovation, Education, and their Social Impact
EditorsAnna Visvizi, Miltiadis D. Lytras
PublisherSpringer
Pages171-179
Number of pages9
ISBN (Print)9783030308087
DOIs
StatePublished - 2019
EventResearch and Innovation Forum, Rii Forum 2019 - Rome, Italy
Duration: 24 Apr 201926 Apr 2019

Publication series

NameSpringer Proceedings in Complexity
ISSN (Print)2213-8684
ISSN (Electronic)2213-8692

Conference

ConferenceResearch and Innovation Forum, Rii Forum 2019
Country/TerritoryItaly
CityRome
Period24/04/1926/04/19

Fingerprint

Dive into the research topics of 'Assessing strategies for sampling dynamic social networks'. Together they form a unique fingerprint.

Cite this