Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Mingzhe Fang"'
Publikováno v:
IEEE Access, Vol 7, Pp 32166-32182 (2019)
The gap between the raw data from various data sources and the diverse intelligent applications has been an obstacle in the field of events analysis in online social networks. Most existing analysis systems focus on data from a certain single online
Externí odkaz:
https://doaj.org/article/e4435cbad51349dbb3e7453384dc7316
Publikováno v:
IEEE Access, Vol 6, Pp 17699-17710 (2018)
Locating the source of information in online social networks facilitates knowing the origins of events, verifying the authenticity of information and finding the initial spreaders of rumors. However, locating the source of information in online socia
Externí odkaz:
https://doaj.org/article/6958458dc4254b53a405bb7c89406e76
Publikováno v:
PLoS ONE, Vol 12, Iss 1, p e0168749 (2017)
The popularity of online information generally experiences a rising and falling evolution. This paper considers the "burst", "peak", and "fade" key events together as a representative summary of popularity evolution. We propose a novel prediction tas
Externí odkaz:
https://doaj.org/article/2ad636e213f640fa87e62d874b1bda4f
Publikováno v:
2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC).
Publikováno v:
IEEE Access, Vol 7, Pp 32166-32182 (2019)
The gap between the raw data from various data sources and the diverse intelligent applications has been an obstacle in the field of events analysis in online social networks. Most existing analysis systems focus on data from a certain single online
Publikováno v:
International Journal of Communication Systems. 31:e3561
Publikováno v:
IIKI
Finding the information source on online social network is called information source locating. However, it is difficult because the structure of social networks is complex and the complete online social network is hard to observe. At the same time, t
Publikováno v:
PLoS ONE, Vol 12, Iss 1, p e0168749 (2017)
PLoS ONE
PLoS ONE
The popularity of online information generally experiences a rising and falling evolution. This paper considers the "burst", "peak", and "fade" key events together as a representative summary of popularity evolution. We propose a novel prediction tas