Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Ritvik Shrivastava"'
Publikováno v:
Communication and Intelligent Systems ISBN: 9789811921292
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6e3cce8b9d7493481dbbf06ad54a7273
https://doi.org/10.1007/978-981-19-2130-8_23
https://doi.org/10.1007/978-981-19-2130-8_23
Publikováno v:
EACL
Detecting arguments in online interactions is useful to understand how conflicts arise and get resolved. Users often use figurative language, such as sarcasm, either as persuasive devices or to attack the opponent by an ad hominem argument. To furthe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::405a585ed5562e58a505bf4a889ce348
http://arxiv.org/abs/2101.10952
http://arxiv.org/abs/2101.10952
Autor:
Bryan Li, Ritvik Shrivastava, Julia Hirschberg, Agustín Gravano, Rose Sloan, Syed Sarfaraz Akhtar
Publikováno v:
10th ISCA Workshop on Speech Synthesis (SSW 10).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a32f5dd5d5cb1d1b4de96f1a107a62bd
https://doi.org/10.21437/ssw.2019-48
https://doi.org/10.21437/ssw.2019-48
Publikováno v:
International Journal of Computational Science and Engineering. 21:69
Existing work in the area of graph classification is mostly restricted to static graphs. These static classification models prove ineffective in several real life scenarios that require an approach capable of handling data of a dynamic nature. Furthe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6d5117afb33e3aebc6eb568898a29e31
https://doi.org/10.1504/ijcse.2020.105214
https://doi.org/10.1504/ijcse.2020.105214
Publikováno v:
Studies in Computational Intelligence ISBN: 9783030054137
COMPLEX NETWORKS (2)
COMPLEX NETWORKS (2)
The hashtag recommendation systems on Twitter have largely focused on analyzing the text content of tweets. In this work, we modify the state-of-the-art existing natural language processing (NLP) technique and deeply ingrain socio-temporal techniques
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2512d17738d649e3be981f90091c7417
https://doi.org/10.1007/978-3-030-05414-4_28
https://doi.org/10.1007/978-3-030-05414-4_28
Publikováno v:
Studies in Computational Intelligence ISBN: 9783030054137
COMPLEX NETWORKS (2)
COMPLEX NETWORKS (2)
We perform a first-of-its-kind characterization of topical homophily - familiarity co-occurring with topic-participation similarity of user pairs - by correlating topic participation similarity and degree of familiarity of users on Twitter. We quanti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::46fb52d1f28099ff5ed5e957135c9f8d
https://doi.org/10.1007/978-3-030-05414-4_29
https://doi.org/10.1007/978-3-030-05414-4_29
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783319769400
ECIR
ECIR
The topical stance detection problem addresses detecting the stance of the text content with respect to a given topic: whether the sentiment of the given text content is in favor of (positive), is against (negative), or is none (neutral) towards the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f28930b866ce55dcf1b89c9185bf9b7f
https://doi.org/10.1007/978-3-319-76941-7_40
https://doi.org/10.1007/978-3-319-76941-7_40
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783319769400
ECIR
ECIR
Topic lifecycle analysis on Twitter, a branch of study that investigates Twitter topics from their birth through lifecycle to death, has gained immense mainstream research popularity. In the literature, topics are often treated as one of (a) hashtags
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7d451f7d65cafad253316a965ccb5312
https://doi.org/10.1007/978-3-319-76941-7_3
https://doi.org/10.1007/978-3-319-76941-7_3
Publikováno v:
Complex Networks & Their Applications VI ISBN: 9783319721491
COMPLEX NETWORKS
COMPLEX NETWORKS
Homophily, the phenomenon of similar people getting connected to and being socially familiar with each other, is well-known on online social networks. Detection of user stance towards given topics, on online social networks, specifically Twitter, has
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d83ed4ffb4adc3de8e4aab6773e943ba
https://doi.org/10.1007/978-3-319-72150-7_68
https://doi.org/10.1007/978-3-319-72150-7_68
Publikováno v:
Complex Networks & Their Applications VI ISBN: 9783319721491
COMPLEX NETWORKS
COMPLEX NETWORKS
Analyzing the lifecycle of topics, that are present in user-generated text content, has emerged as a mainstream topic of social network research. The literature presently identifies topics on Twitter, a prominent online social network, as either indi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::770fb501a066d5a05997fa9f176cf231
https://doi.org/10.1007/978-3-319-72150-7_34
https://doi.org/10.1007/978-3-319-72150-7_34