Zobrazeno 1 - 10
of 35
pro vyhledávání: '"Yozen Liu"'
Autor:
Heinrich Peters, Yozen Liu, Francesco Barbieri, Raiyan Abdul Baten, Sandra C. Matz, Maarten W. Bos
Publikováno v:
Journal of Big Data, Vol 11, Iss 1, Pp 1-20 (2024)
Abstract The success of online social platforms hinges on their ability to predict and understand user behavior at scale. Here, we present data suggesting that context-aware modeling approaches may offer a holistic yet lightweight and potentially pri
Externí odkaz:
https://doaj.org/article/0a2fee6548584d60b2d982b2b6882de4
Autor:
Julie Jiang, Nils Murrugara-Llerena, Maarten W. Bos, Yozen Liu, Neil Shah, Leonardo Neves, Francesco Barbieri
Publikováno v:
Proceedings of the International AAAI Conference on Web and Social Media. 16:393-404
The environment we are in can affect our mood and behavior. One environmental factor is weather, which is linked to sentiment as expressed on social media. However, less is known about how integrating changes in weather, along with time and location
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::452e71970c92d4e6311c77cb3e441bd7
https://doi.org/10.1609/icwsm.v16i1.19301
https://doi.org/10.1609/icwsm.v16i1.19301
Publikováno v:
Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1c7f0f20c6f2235dd4df2d7e78a0fa95
https://doi.org/10.1145/3539597.3570388
https://doi.org/10.1145/3539597.3570388
Culture shapes people's behavior, both online and offline. Surprisingly, there is sparse research on how cultural context affects network formation and content consumption on social media. We analyzed the friendship networks and dyadic relations betw
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bb7312840f9ee95a653e8130df065946
http://arxiv.org/abs/2301.13801
http://arxiv.org/abs/2301.13801
Autor:
Julie Jiang, Ron Dotsch, Mireia Triguero Roura, Yozen Liu, Vítor Silva, Maarten W. Bos, Francesco Barbieri
Pictorial emojis and stickers are commonly used in online social networking to facilitate and aid communications. We delve into the use of Bitmoji stickers, a highly expressive form of pictorial communication using avatars resembling actual users. We
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a4a8541db3d1d0bceca18ede90015825
http://arxiv.org/abs/2211.01426
http://arxiv.org/abs/2211.01426
Autor:
Farhan Asif Chowdhury, Yozen Liu, Koustuv Saha, Nicholas Vincent, Leonardo Neves, Neil Shah, Maarten W. Bos
Publikováno v:
Proceedings of the International AAAI Conference on Web and Social Media. 15:117-128
To improve the user experience as well as business outcomes, social platforms aim to predict user behavior. To this end, recurrent models are often used to predict a user's next behavior based on their most recent behavior. However, people have habit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::aee34980440d5df0dba2466d6ef0bc66
https://doi.org/10.1609/icwsm.v15i1.18046
https://doi.org/10.1609/icwsm.v15i1.18046
Publikováno v:
Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::886389c17e8cd1f8d184ca29aa62451b
https://doi.org/10.1145/3488560.3498398
https://doi.org/10.1145/3488560.3498398
Autor:
Maarten W. Bos, Yozen Liu, Koustuv Saha, Neil Shah, Nicholas Vincent, Farhan Asif Chowdhury, Leonardo Neves
Publikováno v:
CHI
Showing ads delivers revenue for online content distributors, but ad exposure can compromise user experience and cause user fatigue and frustration. Correctly balancing ads with other content is imperative. Currently, ad allocation relies primarily o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ad8962e7d2c12663b40fe0a47650b2ce
https://doi.org/10.1145/3411764.3445394
https://doi.org/10.1145/3411764.3445394
Publikováno v:
WWW
Graph Neural Networks (GNNs) have recently enabled substantial advances in graph learning. Despite their rich representational capacity, GNNs remain under-explored for large-scale social modeling applications. One such industrially ubiquitous applica
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::20a355b13a917f2ae5c3240a579a4385
https://doi.org/10.1145/3442381.3450120
https://doi.org/10.1145/3442381.3450120
Publikováno v:
CIKM
Graph Neural Networks (GNNs) have risen to prominence in learning representations for graph structured data. A single GNN layer typically consists of a feature transformation and a feature aggregation operation. The former normally uses feed-forward
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c0ad3ebcb6a98076c09bd7a3e1ee2edc
http://arxiv.org/abs/2010.01777
http://arxiv.org/abs/2010.01777