User-driven geo-temporal density-based exploration of periodic and not periodic events reported in social networks

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F16%3A10331991" target="_blank" >RIV/00216208:11320/16:10331991 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1016/j.ins.2016.01.014" target="_blank" >http://dx.doi.org/10.1016/j.ins.2016.01.014</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.ins.2016.01.014" target="_blank" >10.1016/j.ins.2016.01.014</a>

Jazyk výsledku

angličtina

Název v původním jazyce

User-driven geo-temporal density-based exploration of periodic and not periodic events reported in social networks

Popis výsledku v původním jazyce

In this paper we propose a procedure consisting of a first collection phase of social network messages, a subsequent user query selection, and finally a clustering phase, defined by extending the density-based DBSCAN algorithm, for performing a geographic and temporal exploration of a collection of items, in order to reveal and map their latent spatio-temporal structure. Specifically, both several geo-temporal distance measures and a density-based geo-temporal clustering algorithm are proposed. The approach can be applied to social messages containing an explicit geographic and temporal location. The algorithm usage is exemplified to identify geographic regions where many geotagged Twitter messages about an event of interest have been created, possibly in the same time period in the case of non-periodic events (aperiodic events), or at regular timestamps in the case of periodic events. This allows discovering the spatio-temporal periodic and aperiodic characteristics of events occurring in specific geographic areas, and thus increasing the awareness of decision makers who are in charge of territorial planning. Several case studies are used to illustrate the proposed procedure.

Název v anglickém jazyce

User-driven geo-temporal density-based exploration of periodic and not periodic events reported in social networks

Popis výsledku anglicky

In this paper we propose a procedure consisting of a first collection phase of social network messages, a subsequent user query selection, and finally a clustering phase, defined by extending the density-based DBSCAN algorithm, for performing a geographic and temporal exploration of a collection of items, in order to reveal and map their latent spatio-temporal structure. Specifically, both several geo-temporal distance measures and a density-based geo-temporal clustering algorithm are proposed. The approach can be applied to social messages containing an explicit geographic and temporal location. The algorithm usage is exemplified to identify geographic regions where many geotagged Twitter messages about an event of interest have been created, possibly in the same time period in the case of non-periodic events (aperiodic events), or at regular timestamps in the case of periodic events. This allows discovering the spatio-temporal periodic and aperiodic characteristics of events occurring in specific geographic areas, and thus increasing the awareness of decision makers who are in charge of territorial planning. Several case studies are used to illustrate the proposed procedure.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

IN - Informatika

OECD FORD obor

—

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2016

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Information Sciences

ISSN

0020-0255

e-ISSN

—

Svazek periodika

340-341

Číslo periodika v rámci svazku

May

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

22

Strana od-do

122-143

Kód UT WoS článku

000371551900008

EID výsledku v databázi Scopus

2-s2.0-84957863065