Details
| Original language | English |
|---|---|
| Pages (from-to) | 5-17 |
| Number of pages | 13 |
| Journal | International Journal on Digital Libraries |
| Volume | 21 |
| Issue number | 1 |
| Early online date | 26 Oct 2018 |
| Publication status | Published - Mar 2020 |
Abstract
How did the popularity of the Greek Prime Minister evolve in 2015? How did the predominant sentiment about him vary during that period? Were there any controversial sub-periods? What other entities were related to him during these periods? To answer these questions, one needs to analyze archived documents and data about the query entities, such as old news articles or social media archives. In particular, user-generated content posted in social networks, like Twitter and Facebook, can be seen as a comprehensive documentation of our society, and thus, meaningful analysis methods over such archived data are of immense value for sociologists, historians, and other interested parties who want to study the history and evolution of entities and events. To this end, in this paper we propose an entity-centric approach to analyze social media archives and we define measures that allow studying how entities were reflected in social media in different time periods and under different aspects, like popularity, attitude, controversiality, and connectedness with other entities. A case study using a large Twitter archive of 4 years illustrates the insights that can be gained by such an entity-centric and multi-aspect analysis.
Keywords
- Entity analytics, Entity linking, Sentiment analysis, Social media archives
ASJC Scopus subject areas
- Social Sciences(all)
- Library and Information Sciences
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In: International Journal on Digital Libraries, Vol. 21, No. 1, 03.2020, p. 5-17.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Tracking the history and evolution of entities
T2 - entity-centric temporal analysis of large social media archives
AU - Fafalios, Pavlos
AU - Iosifidis, Vasileios
AU - Stefanidis, Kostas
AU - Ntoutsi, Eirini
N1 - Funding information: The work was partially funded by the European Commission for the ERC Advanced Grant ALEXANDRIA (No. 339233) and by the German Research Foundation (DFG) project OSCAR (Opinion Stream Classification with Ensembles and Active leaRners).
PY - 2020/3
Y1 - 2020/3
N2 - How did the popularity of the Greek Prime Minister evolve in 2015? How did the predominant sentiment about him vary during that period? Were there any controversial sub-periods? What other entities were related to him during these periods? To answer these questions, one needs to analyze archived documents and data about the query entities, such as old news articles or social media archives. In particular, user-generated content posted in social networks, like Twitter and Facebook, can be seen as a comprehensive documentation of our society, and thus, meaningful analysis methods over such archived data are of immense value for sociologists, historians, and other interested parties who want to study the history and evolution of entities and events. To this end, in this paper we propose an entity-centric approach to analyze social media archives and we define measures that allow studying how entities were reflected in social media in different time periods and under different aspects, like popularity, attitude, controversiality, and connectedness with other entities. A case study using a large Twitter archive of 4 years illustrates the insights that can be gained by such an entity-centric and multi-aspect analysis.
AB - How did the popularity of the Greek Prime Minister evolve in 2015? How did the predominant sentiment about him vary during that period? Were there any controversial sub-periods? What other entities were related to him during these periods? To answer these questions, one needs to analyze archived documents and data about the query entities, such as old news articles or social media archives. In particular, user-generated content posted in social networks, like Twitter and Facebook, can be seen as a comprehensive documentation of our society, and thus, meaningful analysis methods over such archived data are of immense value for sociologists, historians, and other interested parties who want to study the history and evolution of entities and events. To this end, in this paper we propose an entity-centric approach to analyze social media archives and we define measures that allow studying how entities were reflected in social media in different time periods and under different aspects, like popularity, attitude, controversiality, and connectedness with other entities. A case study using a large Twitter archive of 4 years illustrates the insights that can be gained by such an entity-centric and multi-aspect analysis.
KW - Entity analytics
KW - Entity linking
KW - Sentiment analysis
KW - Social media archives
UR - http://www.scopus.com/inward/record.url?scp=85055919931&partnerID=8YFLogxK
U2 - 10.1007/s00799-018-0257-7
DO - 10.1007/s00799-018-0257-7
M3 - Article
AN - SCOPUS:85055919931
VL - 21
SP - 5
EP - 17
JO - International Journal on Digital Libraries
JF - International Journal on Digital Libraries
SN - 1432-5012
IS - 1
ER -