The Experts below are selected from a list of 28305 Experts worldwide ranked by ideXlab platform
Serena Villata - One of the best experts on this subject based on the ideXlab platform.
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argument mining on twitter arguments facts and sources
Empirical Methods in Natural Language Processing, 2017Co-Authors: Mihai Dusmanu, Elena Cabrio, Serena VillataAbstract:Social media collect and spread on the Web personal opinions, facts, fake news and all kind of information users may be interested in. Applying argument mining methods to such heterogeneous data sources is a challenging open research issue, in particular considering the peculiarities of the language used to write textual messages on social media. In addition, new issues emerge when dealing with arguments posted on such platforms, such as the need to make a distinction between personal opinions and actual facts, and to detect the source disseminating information about such facts to allow for provenance verification. In this paper, we apply supervised classification to identify arguments on Twitter, and we present two new tasks for argument mining, namely facts recognition and source identification. We study the feasibility of the approaches proposed to address these tasks on a set of tweets related to the Grexit and Brexit news topics.
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EMNLP - Argument Mining on Twitter: Arguments, Facts and Sources
Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 2017Co-Authors: Mihai Dusmanu, Elena Cabrio, Serena VillataAbstract:Social media collect and spread on the Web personal opinions, facts, fake news and all kind of information users may be interested in. Applying argument mining methods to such heterogeneous data sources is a challenging open research issue, in particular considering the peculiarities of the language used to write textual messages on social media. In addition, new issues emerge when dealing with arguments posted on such platforms, such as the need to make a distinction between personal opinions and actual facts, and to detect the source disseminating information about such facts to allow for provenance verification. In this paper, we apply supervised classification to identify arguments on Twitter, and we present two new tasks for argument mining, namely facts recognition and source identification. We study the feasibility of the approaches proposed to address these tasks on a set of tweets related to the Grexit and Brexit news topics.
Mihai Dusmanu - One of the best experts on this subject based on the ideXlab platform.
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argument mining on twitter arguments facts and sources
Empirical Methods in Natural Language Processing, 2017Co-Authors: Mihai Dusmanu, Elena Cabrio, Serena VillataAbstract:Social media collect and spread on the Web personal opinions, facts, fake news and all kind of information users may be interested in. Applying argument mining methods to such heterogeneous data sources is a challenging open research issue, in particular considering the peculiarities of the language used to write textual messages on social media. In addition, new issues emerge when dealing with arguments posted on such platforms, such as the need to make a distinction between personal opinions and actual facts, and to detect the source disseminating information about such facts to allow for provenance verification. In this paper, we apply supervised classification to identify arguments on Twitter, and we present two new tasks for argument mining, namely facts recognition and source identification. We study the feasibility of the approaches proposed to address these tasks on a set of tweets related to the Grexit and Brexit news topics.
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EMNLP - Argument Mining on Twitter: Arguments, Facts and Sources
Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 2017Co-Authors: Mihai Dusmanu, Elena Cabrio, Serena VillataAbstract:Social media collect and spread on the Web personal opinions, facts, fake news and all kind of information users may be interested in. Applying argument mining methods to such heterogeneous data sources is a challenging open research issue, in particular considering the peculiarities of the language used to write textual messages on social media. In addition, new issues emerge when dealing with arguments posted on such platforms, such as the need to make a distinction between personal opinions and actual facts, and to detect the source disseminating information about such facts to allow for provenance verification. In this paper, we apply supervised classification to identify arguments on Twitter, and we present two new tasks for argument mining, namely facts recognition and source identification. We study the feasibility of the approaches proposed to address these tasks on a set of tweets related to the Grexit and Brexit news topics.
Elena Cabrio - One of the best experts on this subject based on the ideXlab platform.
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argument mining on twitter arguments facts and sources
Empirical Methods in Natural Language Processing, 2017Co-Authors: Mihai Dusmanu, Elena Cabrio, Serena VillataAbstract:Social media collect and spread on the Web personal opinions, facts, fake news and all kind of information users may be interested in. Applying argument mining methods to such heterogeneous data sources is a challenging open research issue, in particular considering the peculiarities of the language used to write textual messages on social media. In addition, new issues emerge when dealing with arguments posted on such platforms, such as the need to make a distinction between personal opinions and actual facts, and to detect the source disseminating information about such facts to allow for provenance verification. In this paper, we apply supervised classification to identify arguments on Twitter, and we present two new tasks for argument mining, namely facts recognition and source identification. We study the feasibility of the approaches proposed to address these tasks on a set of tweets related to the Grexit and Brexit news topics.
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EMNLP - Argument Mining on Twitter: Arguments, Facts and Sources
Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 2017Co-Authors: Mihai Dusmanu, Elena Cabrio, Serena VillataAbstract:Social media collect and spread on the Web personal opinions, facts, fake news and all kind of information users may be interested in. Applying argument mining methods to such heterogeneous data sources is a challenging open research issue, in particular considering the peculiarities of the language used to write textual messages on social media. In addition, new issues emerge when dealing with arguments posted on such platforms, such as the need to make a distinction between personal opinions and actual facts, and to detect the source disseminating information about such facts to allow for provenance verification. In this paper, we apply supervised classification to identify arguments on Twitter, and we present two new tasks for argument mining, namely facts recognition and source identification. We study the feasibility of the approaches proposed to address these tasks on a set of tweets related to the Grexit and Brexit news topics.
Braden T. Warwick - One of the best experts on this subject based on the ideXlab platform.
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Policy Paper: Brexit, Northern Ireland and Ireland
Social Science Research Network, 2016Co-Authors: Sylvia De Mars, Aoife O'donoghue, Colin Murray, Braden T. WarwickAbstract:The general public in Northern Ireland has not been well served by the Brexit debate. The UK debate has been concerned with the implications of Brexit for the UK as a whole, and not on specific issues affecting Northern Ireland. This report focusses on how a Brexit might affect Irish and Northern Irish trade and travel, and the effects that it might have on peace and prosperity.
Sylvia De Mars - One of the best experts on this subject based on the ideXlab platform.
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Policy Paper: Brexit, Northern Ireland and Ireland
Social Science Research Network, 2016Co-Authors: Sylvia De Mars, Aoife O'donoghue, Colin Murray, Braden T. WarwickAbstract:The general public in Northern Ireland has not been well served by the Brexit debate. The UK debate has been concerned with the implications of Brexit for the UK as a whole, and not on specific issues affecting Northern Ireland. This report focusses on how a Brexit might affect Irish and Northern Irish trade and travel, and the effects that it might have on peace and prosperity.
