The task of witness detection in social media is crucial for many practical applications, including rumor debunking, emergency management, and public opinion mining. Yet to date, it has been approached in an approximated way. We propose a method for addressing witness detection in a strict and realistic fashion. By employing hybrid crowdsensing over Twitter, we contact real-life witnesses and use their reactions to build a strong ground-truth, thus avoiding a manual, subjective annotation of the dataset. Using this dataset, we develop a witness detection system based on a machine learning classifier using a wide set of linguistic features and metadata associated with the tweets.
Real-world witness detection in social media via hybrid crowdsensing
Cresci S;Tesconi M;Dell'Orletta F
2018
Abstract
The task of witness detection in social media is crucial for many practical applications, including rumor debunking, emergency management, and public opinion mining. Yet to date, it has been approached in an approximated way. We propose a method for addressing witness detection in a strict and realistic fashion. By employing hybrid crowdsensing over Twitter, we contact real-life witnesses and use their reactions to build a strong ground-truth, thus avoiding a manual, subjective annotation of the dataset. Using this dataset, we develop a witness detection system based on a machine learning classifier using a wide set of linguistic features and metadata associated with the tweets.| Campo DC | Valore | Lingua |
|---|---|---|
| dc.authority.people | Cresci S | it |
| dc.authority.people | Cimino A | it |
| dc.authority.people | Avvenuti M | it |
| dc.authority.people | Tesconi M | it |
| dc.authority.people | Dell'Orletta F | it |
| dc.collection.id.s | 71c7200a-7c5f-4e83-8d57-d3d2ba88f40d | * |
| dc.collection.name | 04.01 Contributo in Atti di convegno | * |
| dc.contributor.appartenenza | Istituto di linguistica computazionale "Antonio Zampolli" - ILC | * |
| dc.contributor.appartenenza.mi | 918 | * |
| dc.date.accessioned | 2024/02/20 17:23:55 | - |
| dc.date.available | 2024/02/20 17:23:55 | - |
| dc.date.issued | 2018 | - |
| dc.description.abstracteng | The task of witness detection in social media is crucial for many practical applications, including rumor debunking, emergency management, and public opinion mining. Yet to date, it has been approached in an approximated way. We propose a method for addressing witness detection in a strict and realistic fashion. By employing hybrid crowdsensing over Twitter, we contact real-life witnesses and use their reactions to build a strong ground-truth, thus avoiding a manual, subjective annotation of the dataset. Using this dataset, we develop a witness detection system based on a machine learning classifier using a wide set of linguistic features and metadata associated with the tweets. | - |
| dc.description.affiliations | Institute of Informatics and Telematics, IIT-CNR, , Italy; Institute of Computational Linguistics, ILC-CNR, , Italy; Department of Information Engineering, University of Pisa, , Italy | - |
| dc.description.allpeople | Cresci, S; Cimino, A; Avvenuti, M; Tesconi, M; Dell'Orletta, F | - |
| dc.description.allpeopleoriginal | Cresci S.; Cimino A.; Avvenuti M.; Tesconi M.; Dell'Orletta F. | - |
| dc.description.fulltext | none | en |
| dc.description.numberofauthors | 5 | - |
| dc.identifier.scopus | 2-s2.0-85050591190 | - |
| dc.identifier.uri | https://hdl.handle.net/20.500.14243/392594 | - |
| dc.identifier.url | http://www.scopus.com/record/display.url?eid=2-s2.0-85050591190&origin=inward | - |
| dc.language.iso | eng | - |
| dc.miur.last.status.update | 2024-12-16T11:57:47Z | * |
| dc.relation.conferencedate | 25-28/06/2018 | - |
| dc.relation.conferencename | 11th edizione del International AAAI Conference on Web and Social Media (ICWSM-18) | - |
| dc.relation.conferenceplace | Stanford (California) | - |
| dc.relation.firstpage | 576 | - |
| dc.relation.lastpage | 579 | - |
| dc.subject.keywords | Witness Detection | - |
| dc.subject.keywords | Social Media Analisys | - |
| dc.subject.singlekeyword | Witness Detection | * |
| dc.subject.singlekeyword | Social Media Analisys | * |
| dc.title | Real-world witness detection in social media via hybrid crowdsensing | en |
| dc.type.driver | info:eu-repo/semantics/conferenceObject | - |
| dc.type.full | 04 Contributo in convegno::04.01 Contributo in Atti di convegno | it |
| dc.type.miur | 273 | - |
| dc.type.referee | Sì, ma tipo non specificato | - |
| dc.ugov.descaux1 | 434925 | - |
| iris.orcid.lastModifiedDate | 2024/04/04 18:24:19 | * |
| iris.orcid.lastModifiedMillisecond | 1712247859712 | * |
| iris.scopus.extIssued | 2018 | - |
| iris.scopus.extTitle | Real-world witness detection in social media via hybrid crowdsensing | - |
| iris.sitodocente.maxattempts | 13 | - |
| scopus.category | 1705 | * |
| scopus.contributor.affiliation | IIT-CNR | - |
| scopus.contributor.affiliation | ILC-CNR | - |
| scopus.contributor.affiliation | University of Pisa | - |
| scopus.contributor.affiliation | IIT-CNR | - |
| scopus.contributor.affiliation | ILC-CNR | - |
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| scopus.contributor.auid | 57540567000 | - |
| scopus.contributor.country | Italy | - |
| scopus.contributor.country | Italy | - |
| scopus.contributor.country | Italy | - |
| scopus.contributor.country | Italy | - |
| scopus.contributor.country | Italy | - |
| scopus.contributor.dptid | 119895528 | - |
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| scopus.contributor.dptid | 119895528 | - |
| scopus.contributor.dptid | 121014396 | - |
| scopus.contributor.name | Stefano | - |
| scopus.contributor.name | Andrea | - |
| scopus.contributor.name | Marco | - |
| scopus.contributor.name | Maurizio | - |
| scopus.contributor.name | Felice | - |
| scopus.contributor.subaffiliation | Institute of Informatics and Telematics; | - |
| scopus.contributor.subaffiliation | Institute of Computational Linguistics; | - |
| scopus.contributor.subaffiliation | Department of Information Engineering; | - |
| scopus.contributor.subaffiliation | Institute of Informatics and Telematics; | - |
| scopus.contributor.subaffiliation | Institute of Computational Linguistics; | - |
| scopus.contributor.surname | Cresci | - |
| scopus.contributor.surname | Cimino | - |
| scopus.contributor.surname | Avvenuti | - |
| scopus.contributor.surname | Tesconi | - |
| scopus.contributor.surname | Dell'Orletta | - |
| scopus.date.issued | 2018 | * |
| scopus.description.abstracteng | The task of witness detection in social media is crucial for many practical applications, including rumor debunking, emergency management, and public opinion mining. Yet to date, it has been approached in an approximated way. We propose a method for addressing witness detection in a strict and realistic fashion. By employing hybrid crowdsensing over Twitter, we contact real-life witnesses and use their reactions to build a strong ground-truth, thus avoiding a manual, subjective annotation of the dataset. Using this dataset, we develop a witness detection system based on a machine learning classifier using a wide set of linguistic features and metadata associated with the tweets. | * |
| scopus.description.allpeopleoriginal | Cresci S.; Cimino A.; Avvenuti M.; Tesconi M.; Dell'Orletta F. | * |
| scopus.differences | scopus.relation.conferencename | * |
| scopus.differences | scopus.publisher.name | * |
| scopus.differences | scopus.relation.conferencedate | * |
| scopus.differences | scopus.identifier.isbn | * |
| scopus.differences | scopus.relation.conferenceplace | * |
| scopus.document.type | cp | * |
| scopus.document.types | cp | * |
| scopus.funding.funders | 501100003407 - Ministero dell’Istruzione, dell’Università e della Ricerca; 501100009888 - Regione Toscana; | * |
| scopus.identifier.isbn | 9781577357988 | * |
| scopus.identifier.pui | 623270010 | * |
| scopus.identifier.scopus | 2-s2.0-85050591190 | * |
| scopus.journal.sourceid | 21100893949 | * |
| scopus.language.iso | eng | * |
| scopus.publisher.name | AAAI Press | * |
| scopus.relation.conferencedate | 2018 | * |
| scopus.relation.conferencename | 12th International AAAI Conference on Web and Social Media, ICWSM 2018 | * |
| scopus.relation.conferenceplace | Stanford University, usa | * |
| scopus.relation.firstpage | 576 | * |
| scopus.relation.lastpage | 579 | * |
| scopus.title | Real-world witness detection in social media via hybrid crowdsensing | * |
| scopus.titleeng | Real-world witness detection in social media via hybrid crowdsensing | * |
| Appare nelle tipologie: | 04.01 Contributo in Atti di convegno | |
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