@techreport{oai:ipsj.ixsq.nii.ac.jp:00211799,
 author = {Teklu, Aregawi Gidey and Toshiyuki, Amagasa and Teklu, Aregawi Gidey and Toshiyuki, Amagasa},
 issue = {7},
 month = {Jul},
 note = {In recent years, Social Network Service has gained much public attention as a source of information. Twitter is considered as most prominent SNS source. Most of previous studies on the content of tweets have focused on the detection of emerging topics and some have focused on creation of RDF. It is important to generate RDF metadata from tweets to put data in context via linking and semantic metadata providing a framework for data integration, analytics and sharing. However, in the previous studies, the generated RDFs were not from streaming tweets and the mentions interlinked with knowledge graphs did not show the location of the text in the tweet. In our experiment, we generated RDF metadata from streaming tweets using a hashtag 'Covid-19' and we located the exact position of the mentions in the tweet being linked to a knowledge graph, WikiPedia using TagMe entity linker. We expressed it as a URI which includes the URL of Twitter, the user name, the tweet id and index of the offset information., In recent years, Social Network Service has gained much public attention as a source of information. Twitter is considered as most prominent SNS source. Most of previous studies on the content of tweets have focused on the detection of emerging topics and some have focused on creation of RDF. It is important to generate RDF metadata from tweets to put data in context via linking and semantic metadata providing a framework for data integration, analytics and sharing. However, in the previous studies, the generated RDFs were not from streaming tweets and the mentions interlinked with knowledge graphs did not show the location of the text in the tweet. In our experiment, we generated RDF metadata from streaming tweets using a hashtag 'Covid-19' and we located the exact position of the mentions in the tweet being linked to a knowledge graph, WikiPedia using TagMe entity linker. We expressed it as a URI which includes the URL of Twitter, the user name, the tweet id and index of the offset information.},
 title = {Generating RDF Metadata from Twitter Streams},
 year = {2021}
}