TY - GEN
T1 - Shout out
AU - Gandy, Lisa M.
AU - Nichols, Nathan D.
AU - Hammond, Kristian J.
PY - 2010
Y1 - 2010
N2 - A useful approach for enabling computers to automatically create new content is utilizing the text, media, and information already present on the World Wide Web. The newly created content is known as "machine-generated content". For example, a machine-generated content system may create a multimedia news show with two animated anchors presenting a news story; one anchor reads the news story with text taken from an existing news article, and the other anchor regularly interrupts with his or her own opinion about the story. In this paper, we present such a system, and describe in detail its strategy for autonomously extracting and selecting the opinions given by the second anchor.
AB - A useful approach for enabling computers to automatically create new content is utilizing the text, media, and information already present on the World Wide Web. The newly created content is known as "machine-generated content". For example, a machine-generated content system may create a multimedia news show with two animated anchors presenting a news story; one anchor reads the news story with text taken from an existing news article, and the other anchor regularly interrupts with his or her own opinion about the story. In this paper, we present such a system, and describe in detail its strategy for autonomously extracting and selecting the opinions given by the second anchor.
KW - cosine similarity
KW - emotional valence detection
KW - machine-generated content
UR - http://www.scopus.com/inward/record.url?scp=77954575637&partnerID=8YFLogxK
U2 - 10.1145/1772690.1772821
DO - 10.1145/1772690.1772821
M3 - Conference contribution
AN - SCOPUS:77954575637
SN - 9781605587998
T3 - Proceedings of the 19th International Conference on World Wide Web, WWW '10
SP - 1095
EP - 1096
BT - Proceedings of the 19th International Conference on World Wide Web, WWW '10
Y2 - 26 April 2010 through 30 April 2010
ER -