TY - GEN
T1 - Towards linked data for wikidata revisions and twitter trending hashtags
AU - Dooley, Paula
AU - Božic, Bojan
N1 - Publisher Copyright:
© 2019 Association for Computing Machinery.
PY - 2019/12/2
Y1 - 2019/12/2
N2 - This paper uses Twitter as a microblogging platform to link hashtags, which relate the message to a topic that is shared among users, to Wikidata, a central knowledge base of information relying on its members and machine bots to keeping its content up to date. The data is stored in a highly structured format, with the added SPARQL Protocol And RDF Query Language (SPARQL) endpoint to allow users to query its knowledge base. Our research, designs and implements a process to stream live Twitter tweets and to parse existing Wikidata revision XML files provided by Wikidata. Furthermore, we identify if a correlation exists between the top Twitter hashtags and Wikidata revisions over a seventy-seven-day period.We have used statistical evaluation tools, such as 'Jaccard Ratio' and 'Kolmogorov-Smirnov' to investigate a significant statistical correlation between Twitter hashtags and Wikidata revisions over the studied period.
AB - This paper uses Twitter as a microblogging platform to link hashtags, which relate the message to a topic that is shared among users, to Wikidata, a central knowledge base of information relying on its members and machine bots to keeping its content up to date. The data is stored in a highly structured format, with the added SPARQL Protocol And RDF Query Language (SPARQL) endpoint to allow users to query its knowledge base. Our research, designs and implements a process to stream live Twitter tweets and to parse existing Wikidata revision XML files provided by Wikidata. Furthermore, we identify if a correlation exists between the top Twitter hashtags and Wikidata revisions over a seventy-seven-day period.We have used statistical evaluation tools, such as 'Jaccard Ratio' and 'Kolmogorov-Smirnov' to investigate a significant statistical correlation between Twitter hashtags and Wikidata revisions over the studied period.
KW - Hashtags
KW - Jaccard Ratio
KW - Kolmogorov-Smirnov
KW - Microblogging
KW - SPARQL
KW - Trending
KW - Twitter
KW - Wikidata
UR - https://www.scopus.com/pages/publications/85123040112
U2 - 10.1145/3366030.3366048
DO - 10.1145/3366030.3366048
M3 - Conference contribution
AN - SCOPUS:85123040112
T3 - ACM International Conference Proceeding Series
BT - 21st International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2019 - Proceedings
A2 - Indrawan-Santiago, Maria
A2 - Pardede, Eric
A2 - Salvadori, Ivan Luiz
A2 - Steinbauer, Matthias
A2 - Khalil, Ismail
A2 - Anderst-Kotsis, Gabriele
PB - Association for Computing Machinery (ACM)
T2 - 21st International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2019
Y2 - 2 December 2019 through 4 December 2019
ER -