This work focuses on the analysis of Italian social media messages for disaster management and aims at the detection of messages carrying critical information for the damage assessment task. A main novelty of this study consists in the focus on out-domain and cross-event damage detection, and on the investigation of the most relevant tweet-derived features for these tasks. We devised different experiments by resorting to a wide set of linguistic features qualifying the lexical and grammatical structure of a text as well as ad-hoc features specifically implemented for this task. We investigated the most effective features that allow to achieve the best results. A further result of this study is the construction of the first manually annotated Italian corpus of social media messages for damage assessment.
A Linguistically-driven Approach to Cross-Event Damage Assessment of Natural Disasters from Social Media Messages
S Cresci;M Tesconi;F Dell'Orletta
2015
Abstract
This work focuses on the analysis of Italian social media messages for disaster management and aims at the detection of messages carrying critical information for the damage assessment task. A main novelty of this study consists in the focus on out-domain and cross-event damage detection, and on the investigation of the most relevant tweet-derived features for these tasks. We devised different experiments by resorting to a wide set of linguistic features qualifying the lexical and grammatical structure of a text as well as ad-hoc features specifically implemented for this task. We investigated the most effective features that allow to achieve the best results. A further result of this study is the construction of the first manually annotated Italian corpus of social media messages for damage assessment.| Campo DC | Valore | Lingua |
|---|---|---|
| dc.authority.orgunit | Istituto di informatica e telematica - IIT | - |
| dc.authority.orgunit | Istituto di linguistica computazionale "Antonio Zampolli" - ILC | - |
| dc.authority.people | S Cresci | it |
| dc.authority.people | M Tesconi | it |
| dc.authority.people | A Cimino | it |
| dc.authority.people | F Dell'Orletta | 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 informatica e telematica - IIT | * |
| dc.contributor.appartenenza | Istituto di linguistica computazionale "Antonio Zampolli" - ILC | * |
| dc.contributor.appartenenza.mi | 912 | * |
| dc.contributor.appartenenza.mi | 918 | * |
| dc.date.accessioned | 2024/02/18 23:09:06 | - |
| dc.date.available | 2024/02/18 23:09:06 | - |
| dc.date.issued | 2015 | - |
| dc.description.abstracteng | This work focuses on the analysis of Italian social media messages for disaster management and aims at the detection of messages carrying critical information for the damage assessment task. A main novelty of this study consists in the focus on out-domain and cross-event damage detection, and on the investigation of the most relevant tweet-derived features for these tasks. We devised different experiments by resorting to a wide set of linguistic features qualifying the lexical and grammatical structure of a text as well as ad-hoc features specifically implemented for this task. We investigated the most effective features that allow to achieve the best results. A further result of this study is the construction of the first manually annotated Italian corpus of social media messages for damage assessment. | - |
| dc.description.affiliations | CNR-IIT, Pisa, Italy; CNR-IIT, Pisa, Italy; CNR-ILC, Pisa, Italy; CNR-ILC, Pisa, Italy | - |
| dc.description.allpeople | S. Cresci; M. Tesconi; A. Cimino; F. Dell'Orletta | - |
| dc.description.allpeopleoriginal | S. Cresci, M. Tesconi, A. Cimino, F. Dell'Orletta | - |
| dc.description.fulltext | none | en |
| dc.description.numberofauthors | 3 | - |
| dc.identifier.uri | https://hdl.handle.net/20.500.14243/271161 | - |
| dc.language.iso | eng | - |
| dc.relation.conferencedate | 18/05/2015 | - |
| dc.relation.conferencename | Proceedings of the 24th international conference companion on World Wide Web. ACM, 2015. | - |
| dc.relation.conferenceplace | Florence, Italy | - |
| dc.relation.numberofpages | 6 | - |
| dc.subject.keywords | crisis informatics | - |
| dc.subject.keywords | Damage assessment | - |
| dc.subject.keywords | Emergency Management | - |
| dc.subject.keywords | feature selection | - |
| dc.subject.keywords | social media mining | - |
| dc.subject.keywords | Social Sensing | - |
| dc.subject.singlekeyword | crisis informatics | * |
| dc.subject.singlekeyword | Damage assessment | * |
| dc.subject.singlekeyword | Emergency Management | * |
| dc.subject.singlekeyword | feature selection | * |
| dc.subject.singlekeyword | social media mining | * |
| dc.subject.singlekeyword | Social Sensing | * |
| dc.title | A Linguistically-driven Approach to Cross-Event Damage Assessment of Natural Disasters from Social Media Messages | 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 | 336952 | - |
| iris.orcid.lastModifiedDate | 2024/03/01 14:45:18 | * |
| iris.orcid.lastModifiedMillisecond | 1709300718064 | * |
| iris.scopus.extIssued | 2015 | - |
| iris.scopus.extTitle | A linguistically-driven approach to cross-event damage assessment of natural disasters from social media messages | - |
| iris.sitodocente.maxattempts | 1 | - |
| Appare nelle tipologie: | 04.01 Contributo in Atti di convegno | |
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