IRIS
HOVY, DIRK
 Distribuzione geografica
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Continente #
EU - Europa 5.552
NA - Nord America 3.899
AS - Asia 2.099
SA - Sud America 209
AF - Africa 25
OC - Oceania 13
Continente sconosciuto - Info sul continente non disponibili 8
Totale 11.805
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Nazione #
US - Stati Uniti d'America 3.709
IT - Italia 1.166
DE - Germania 970
IE - Irlanda 923
RU - Federazione Russa 734
SG - Singapore 599
CN - Cina 551
GB - Regno Unito 483
UA - Ucraina 322
FR - Francia 265
TR - Turchia 237
SE - Svezia 216
HK - Hong Kong 215
BR - Brasile 171
CA - Canada 160
FI - Finlandia 135
IL - Israele 108
IN - India 85
VN - Vietnam 85
ID - Indonesia 73
CZ - Repubblica Ceca 66
BG - Bulgaria 43
NL - Olanda 37
CH - Svizzera 32
AT - Austria 28
JP - Giappone 28
IR - Iran 23
DK - Danimarca 21
BE - Belgio 17
RO - Romania 17
KR - Corea 16
ES - Italia 15
MX - Messico 14
PL - Polonia 14
AU - Australia 12
PK - Pakistan 12
PH - Filippine 10
AR - Argentina 9
PT - Portogallo 9
SC - Seychelles 9
AE - Emirati Arabi Uniti 8
BD - Bangladesh 8
EU - Europa 8
SK - Slovacchia (Repubblica Slovacca) 8
MY - Malesia 7
HU - Ungheria 6
JM - Giamaica 6
PE - Perù 6
VE - Venezuela 6
CL - Cile 5
CO - Colombia 5
GR - Grecia 5
KG - Kirghizistan 5
MA - Marocco 5
NO - Norvegia 5
AZ - Azerbaigian 4
EC - Ecuador 4
EE - Estonia 4
MT - Malta 4
PA - Panama 4
AM - Armenia 3
CR - Costa Rica 3
KZ - Kazakistan 3
TH - Thailandia 3
UZ - Uzbekistan 3
ZA - Sudafrica 3
BO - Bolivia 2
DO - Repubblica Dominicana 2
DZ - Algeria 2
EG - Egitto 2
GE - Georgia 2
IQ - Iraq 2
JO - Giordania 2
LK - Sri Lanka 2
LT - Lituania 2
LU - Lussemburgo 2
TW - Taiwan 2
AO - Angola 1
BY - Bielorussia 1
HR - Croazia 1
KE - Kenya 1
KH - Cambogia 1
LA - Repubblica Popolare Democratica del Laos 1
NI - Nicaragua 1
NZ - Nuova Zelanda 1
SA - Arabia Saudita 1
SI - Slovenia 1
TN - Tunisia 1
UG - Uganda 1
UY - Uruguay 1
Totale 11.805
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Città #
Dublin 906
Frankfurt am Main 614
Milan 463
Ann Arbor 410
Chandler 402
Houston 322
Jacksonville 269
Singapore 245
Southend 227
Ashburn 213
Hong Kong 200
Moscow 197
Toronto 142
Izmir 137
Beijing 131
Helsinki 120
Woodbridge 120
Wilmington 104
The Dalles 103
Dearborn 97
Boardman 89
Boston 78
Lawrence 74
Fairfield 71
Dong Ket 70
Jakarta 69
New York 69
Seattle 64
Modena 63
Redwood City 50
Ladispoli 48
Rome 45
Tel Aviv 45
Mumbai 44
Brno 41
Los Angeles 37
London 32
Cambridge 30
Mountain View 29
Chicago 27
Munich 27
Düsseldorf 26
Philadelphia 23
Mainz 21
Nanjing 21
Nuremberg 21
Braunschweig 20
Grafing 20
Hefei 18
Redmond 16
Robbiate 16
São Paulo 16
Vienna 16
Zurich 16
Brussels 13
Bucharest 13
Norwalk 13
Paris 13
Washington 13
Edison 12
Lappeenranta 12
North Bergen 12
Shanghai 12
Tokyo 12
Guangzhou 11
Kunming 11
Palombara Sabina 11
Trento 11
Assago 10
Fremont 10
Turin 10
Bexley 9
Delhi 9
Lauterbourg 9
Mexico City 9
Santa Clara 9
Amsterdam 8
Bratislava 8
Portsmouth 8
Xi'an 8
Bonndorf 7
Buffalo 7
Darmstadt 7
Dubai 7
Falkenstein 7
Falls Church 7
Jinan 7
Pavia 7
Serra 7
Tavagnacco 7
Udine 7
Warsaw 7
Acton 6
Bologna 6
Bolzano 6
Brooklyn 6
Casorate Primo 6
Geelong 6
Grenoble 6
Heidenau 6
Totale 7.182
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Nome #
Hateful symbols or hateful people? Predictive features for hate speech detection on Twitter 322
Capturing regional variation with distributed place representations and geographic retrofitting 281
Personality traits on Twitter - or - how to get 1.500 personality tests in a week 261
Visualizing regional language variation across Europe on Twitter 244
What's in a preposition? Dimensions of sense disambiguation for an interesting word class 231
Challenges of studying and processing dialects in social media 226
Hey Siri. Ok Google. Alexa: a topic modeling of user reviews for smart speakers 211
User review sites as a resource for large-scale sociolinguistic studies 210
More or less supervised supersense tagging of Twitter 208
Geolocation with attention-based multitask learning models 200
Dense node representation for geolocation 189
Comparing Bayesian models of annotation 188
Identifying linguistic areas for geolocation 187
Models and training for unsupervised preposition sense disambiguation 182
Increasing in-class similarity by retrofitting embeddings with demographic information 176
Women’s syntactic resilience and men’s grammatical luck: gender-bias in part-of-speech tagging and dependency parsing 175
The social and the neural network: how to make natural language processing about people again 175
Helpful or hierarchical? Predicting the communicative strategies of chat participants, and their impact on success 167
Text analysis in Python for social scientists: discovery and exploration 167
Computerlingvistik. Metoder til visualisering af regional variation i sociale medier 163
Linguistically debatable or just plain wrong? 159
Text analysis in Python for social scientists : prediction and classification 159
Putting sarcasm detection into context: the effects of class imbalance and manual labelling on supervised machine classification of Twitter conversations 152
Lörres, Möppes, and the Swiss. (Re)Discovering regional patterns in anonymous social media data 152
HONEST: measuring hurtful sentence completion in language models 149
Exploring language variation across Europe: a web-based tool for computational sociolinguistics 141
The social impact of natural language processing 140
Predicting news headline popularity with syntactic and semantic knowledge using multi-task learning 139
Tagging performance correlates negatively with author age 137
What’s in a p-value in NLP? 136
Crowdsourcing and annotating NER for Twitter# drift 136
The rating game: sentiment rating reproducibility from text 134
Experiments with crowdsourced re-annotation of a POS tagging data set 133
FEEL-IT: emotion and sentiment classification for the Italian language 131
Analysis and modeling of "focus" in context 130
The enemy in your own camp: how well can we detect statistically-generated fake reviews-an adversarial study 129
Disambiguation of preposition sense using linguistically motivated features 128
Unsupervised discovery of domain-specific knowledge from text 127
Five sources of bias in natural language processing 126
Copenhagen-Malm"o: Tree approximations of semantic parsing problems 125
A Walk-Based Semantically Enriched Tree Kernel Over Distributed Word Representations 125
A case for soft loss functions 125
Learning a POS tagger for AAVE-like language 122
Learning whom to trust with MACE 121
When POS data sets don’t add up: Combatting sample bias 121
Cross-lingual syntactic variation over age and gender 118
Demographic factors improve classification performance 117
Identifying metaphorical word use with tree kernels 116
Augmenting English adjective senses with supersenses 116
Cross-lingual contextualized topic models with zero-shot learning 116
Adapting taggers to Twitter with not-so-distant supervision 114
End-to-end information extraction without token-level supervision 114
How Well can We Learn Interpretable Entity Types from Text? 113
Mining for unambiguous instances to adapt part-of-speech taggers to new domains 105
Multitask learning for mental health conditions with limited social media data 105
Unsupervised mining of lexical variants from noisy text 104
Solving electrical networks to incorporate supervision in random walks 104
MilaNLP @ WASSA: does BERT feel sad when you cry? 99
“You sound just like your father”. Commercial machine translation systems include stylistic biases 98
When did that happen? Linking events and relations to timestamps 96
BERTective: language models and contextual information for deception detection 95
Learning part-of-speech taggers with inter-annotator agreement loss 93
If all you have is a bit of the Bible: learning POS taggers for truly low-resource languages 87
Entropy-based attention regularization frees unintended bias mitigation from lists 85
Gender and age bias in commercial machine translation 82
Robust Cross-Domain Sentiment Analysis for Low-Resource Languages 82
Beyond black & white: leveraging annotator disagreement via soft-label multi-task learning 80
"It's not just hate": a multi-dimensional perspective on detecting harmful speech online 78
Predictive biases in natural language processing models: a conceptual framework and overview 77
Proceedings of the Fourth Workshop on Natural Language Processing and Computational Social Sciences (NLP+CSS) 77
On the gap between adoption and understanding in NLP 77
“We will reduce taxes” - Identifying election pledges with language models 76
Viewpoint: Artificial Intelligence accidents waiting to happen? 74
Hard and soft evaluation of NLP models with BOOtSTrap SAmpling - BooStSa 71
Pre-training is a hot topic: contextualized document embeddings improve topic coherence 71
ProSiT! Latent Variable Discovery with PROgressive SImilarity Thresholds 70
We need to consider disagreement in evaluation 70
Wordify: a tool for discovering and differentiating consumer vocabularies 69
Beyond digital "echo chambers": the role of viewpoint diversity in political discussion 67
Data-efficient strategies for expanding hate speech detection into under-resourced languages 64
DADIT: a dataset for demographic classification of Italian Twitter users and a comparison of prediction methods 63
What about em? How commercial Machine Translation fails to handle (neo-)pronouns 60
SafetyKit: first aid for measuring safety in open-domain conversational systems 60
Learning from disagreement: a survey 60
Universal joy: a data set and results for classifying emotions across languages 55
The importance of modeling social factors of language: theory and practice 54
Bridging fairness and environmental sustainability in natural language processing 53
Benchmarking post-hoc interpretability approaches for transformer-based misogyny detection 52
Beyond the stats: realities, perception, and social media discourse on poverty 52
Two contrasting data annotation paradigms for subjective NLP tasks 51
Language invariant properties in Natural Language Processing 49
Measuring harmful sentence completion in language models for LGBTQIA+ individuals 48
Welcome to the modern world of pronouns: identity-inclusive Natural Language Processing beyond gender 47
SocioProbe: what, when, and where language models learn about sociodemographics 46
XLM-EMO: multilingual emotion prediction in social media text 45
Wisdom of instruction-tuned language model crowds. Exploring model label variation 43
Guiding the release of safer E2E conversational AI through value sensitive design 42
MilaNLP at SemEval-2023 Task 10: ensembling domain-adapted and regularized pretrained language models for robust sexism detection 38
Can demographic factors improve text classification? Revisiting demographic adaptation in the age of transformers 36
Pipelines for social bias testing of large language models 35
Totale 11.709
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Categoria #
all - tutte 56.054
article - articoli 0
book - libri 0
conference - conferenze 0
curatela - curatele 0
other - altro 0
patent - brevetti 0
selected - selezionate 0
volume - volumi 0
Totale 56.054
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Totale Lug Ago Sett Ott Nov Dic Gen Feb Mar Apr Mag Giu
2019/2020198 0 0 0 0 0 0 0 0 0 0 119 79
2020/20211.285 72 113 162 80 163 62 145 78 106 106 85 113
2021/2022981 59 199 17 58 96 98 44 105 72 38 102 93
2022/20232.974 209 195 169 312 227 190 91 148 1.170 102 84 77
2023/20241.987 104 122 130 107 215 199 177 229 75 90 196 343
2024/20252.727 84 77 167 71 140 122 344 303 976 267 176 0
Totale 12.166