Áreas de investigación
Sociology and Political Science
Energy Engineering and Power Technology
Electrical and Electronic Engineering
Theoretical Computer Science
Control and Optimization
Computer Science (miscellaneous)
Métricas
50
Publicaciones
461
Citaciones
10
H-index
4
H5-index
1.75
FCWI
`
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| # | Título | Citaciones | Año de publicación |
|---|---|---|---|
| 1 |
Sign-Regularized Multi-Task Learning |
1 |
2023 |
| 2 |
Preface |
0 |
2023 |
| 3 |
Estimating urban socioeconomic inequalities through airtime top-up transactions data |
3 |
2021 |
| 4 |
Seq2Seq models for recommending short text conversations |
10 |
2020 |
| 5 |
The keyword to success: Comparative analysis of Computer Science research across representative universities in Latin America |
1 |
2020 |
| 6 |
Temporal topics in online news articles: Migration crisis in Venezuela |
1 |
2020 |
| 7 |
Spatio-temporal Analysis: Using Instagram Posts to Characterize Urban Point-of-interest |
5 |
2020 |
| 8 |
Tech for Hire: Data Science-Related Jobs Signal Economic Growth |
1 |
2020 |
| 9 |
Quantifying the impact of a natural disaster on retail stores' customer behavior: The case of Ecuador |
1 |
2020 |
| 10 |
A Place to Go: Locating Damaged Regions After Natural Disasters Through Mobile Phone Data |
1 |
2020 |
| 11 |
Mining top-up transactions and online classified ads to predict urban neighborhoods socioeconomic status |
6 |
2019 |
| 12 |
Cross-lingual perspectives about crisis-related conversations on twitter |
3 |
2019 |
| 13 |
Digital transactions mining to characterize temporal rhythms of a city |
2 |
2019 |
| 14 |
The good, the bad and the ugly: Workers profiling through clustering analysis |
1 |
2019 |
| 15 |
JTML at SemEval-2019 task 6: Offensive tweets identification using convolutional neural networks |
2 |
2019 |
| 16 |
IEEE Access Special Section Editorial: Social Computing Applications for Smart Cities |
0 |
2019 |
| 17 |
Neural semi-supervised learning for multi-labeled short-texts |
1 |
2019 |
| 18 |
Who You Should Not Follow: Extracting Word Embeddings from Tweets to Identify Groups of Interest and Hijackers in Demonstrations |
14 |
2019 |
| 19 |
Organ identification on shrimp histological images: A comparative study considering CNN and feature engineering |
5 |
2018 |
| 20 |
RiSC: Quantifying change after natural disasters to estimate infrastructure damage with mobile phone data |
12 |
2018 |
| 21 |
Know your customer: Detection of Customer Experience (CX) in Social Platforms using Text Categorization |
0 |
2018 |
| 22 |
Mining Worldwide Entrepreneurs Psycholinguistic Dimensions from Twitter |
4 |
2018 |
| 23 |
The Silence of the Cantons: Estimating Villages Socioeconomic Status Through Mobile Phones Data |
6 |
2018 |
| 24 |
Uncovering aspects of places for fitness activities through social media |
2 |
2018 |
| 25 |
Where to go in Brooklyn: NYC mobility patterns from taxi rides |
4 |
2018 |
| 26 |
National leaders' twitter speech to infer political leaning and election results in 2015 Venezuelan parliamentary elections |
5 |
2017 |
| 27 |
What ignites a reply? Characterizing conversations in microblogs |
3 |
2017 |
| 28 |
Back to #6D: Predicting Venezuelan states political election results through Twitter |
21 |
2017 |
| 29 |
Requiem for online harassers: Identifying racism from political tweets |
7 |
2017 |
| 30 |
Crisis management on Twitter: Detecting emerging leaders |
7 |
2017 |
| 31 |
Secrets of Quito: Discovering a city through TripAdvisor |
3 |
2017 |
| 32 |
Scientific communities detection and analysis in the bibliographic database: SCOPUS |
6 |
2017 |
| 33 |
Milano, città d' arte: Urban residents preferences clusters from tweets |
1 |
2017 |
| 34 |
E-Health and fitness in Ecuador: A social media based analysis |
5 |
2017 |
| 35 |
ProximityRank: Who are the nearest influencers? |
1 |
2017 |
| 36 |
Affinity groups: A linguistic analysis for social network groups identification |
0 |
2017 |
| 37 |
Linguistic profiles on microblogging platforms to characterize political leaders: The Ecuadorian case on Twitter |
5 |
2016 |
| 38 |
Clustering of EEG occipital signals using k-means |
4 |
2016 |
| 39 |
Characterizing influential leaders of Ecuador on Twitter using computational intelligence |
1 |
2016 |
| 40 |
Geo-localized social media data to improve characterization of international travelers |
5 |
2016 |
| 41 |
Scalable urban data collection from the web |
4 |
2016 |
| 42 |
Taxonomy-based discovery and annotation of functional areas in the city |
23 |
2015 |
| 43 |
Taking Brazil's pulse: Tracking growing urban economies from online attention |
6 |
2014 |
| 44 |
A time-based collective factorization for topic discovery and monitoring in news |
63 |
2014 |
| 45 |
Modeling dynamics of attention in social media with user efficiency |
12 |
2014 |
| 46 |
Tracking human migration from online attention |
2 |
2014 |
| 47 |
Putting humans in the loop: Social computing for Water Resources Management |
59 |
2012 |
| 48 |
Combining social Web and BPM for improving enterprise performances: The BPM4People approach to Social BPM |
57 |
2012 |
| 49 |
BPMN and design patterns for engineering social BPM solutions |
51 |
2012 |
| 50 |
A notation for supporting social business process modeling |
24 |
2011 |