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Leveraging Social Media Data to Understand the Impact of COVID-19 on Residents' Dietary Behaviors: Observational Study

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Journal of Medical Internet Research 2025年 27卷 e51638页

作者： Chuqin Li Alexis Jordan Yaorong Ge Albert Park Department of Software and Information Systems College of Computing and Informatics University of North Carolina Charlotte NC United States School of Data Science College of Computing and Informatics University of North Carolina Charlotte NC United States

Background The COVID-19 pandemic has inflicted global devastation, infecting over 750 million and causing 6 million deaths. In an effort to control the spread of the virus, governments around the world implemented a variety of measures, including stay-at-home orders, school closures, and mask mandates. These measures had a substantial impact on dietary behavior, with individuals discussing more home-cooked meals and snacking on social media. Objective The study explores pandemic-induced dietary behavior changes using Twitter images and text, particularly in relation to obesity, to inform interventions and understand societal influences on eating habits. Additionally, the study investigates the impact of COVID-19 on emotions and eating patterns. Methods In this study, we collected approximately 200,000 tweets related to food between May and July in 2019, 2020, and 2021. We used transfer learning and a pretrained ResNet-101 neural network to classify images into 4 health categories: definitely healthy, healthy, unhealthy, and definitely unhealthy. We then used the state obesity rates from the Behavioral Risk Factor Surveillance System (BRFSS) to assess the correlation between state obesity rates and dietary images on Twitter. The study further investigates the effects of COVID-19 on emotional changes and their relation to eating patterns via sentiment analysis. Furthermore, we illustrated how the popularity of meal terms and health categories changed over time, considering varying time zones by incorporating geolocation data. Results A significant correlation was observed between state obesity rates and the percentages of definitely healthy ( r =–0.360, P =.01) and definitely unhealthy ( r =0.306, P =.03) food images in 2019. However, no trend was observed in 2020 and 2021, despite higher obesity rates. A significant ( P <.001) increase in the percentage of healthy food consumption was observed during (39.99% in 2020) and after the shutdown (39.32% in 2021), as compar

关键词： social media obesity COVID-19 dietary pattern observational study dietary behaviors Twitter tweets eating patterns food consumption social media data

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OMR-ASSISTED TRANSCRIPTION: A CASE STUDY WITH EARLY PRINTS 22

OMR-ASSISTED TRANSCRIPTION: A CASE STUDY WITH EARLY PRINTS

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22nd International Conference on Music Information Retrieval, ISMIR 2021

作者： Alfaro-Contreras, María Rizo, David Iñesta, Jose M. Calvo-Zaragoza, Jorge Department of Software and Computing Systems University of Alicante Spain

ISBN: (纸本)9781732729902

Most of the musical heritage is only available as physical documents, given that the engraving process was carried out by handwriting or typesetting until the end of the 20th century. Their mere availability as scanned images does not enable tasks such as indexing or editing unless they are transcribed into a structured digital format. Given the cost and time required for manual transcription, Optical Music Recognition (OMR) presents itself as a promising alternative. Quite often, OMR systems show acceptable but not perfect performance, which eventually leaves them out of the transcription process. On the assumption that OMR systems might always make some errors, it is essential that the user corrects the output. This paper contributes to a better understanding of how music transcription is improved by the assistance of OMR systems that include the end-user in the recognition process. For that, we have measured the transcription time of a printed early music work under two scenarios: a manual one and a state-of-the-art OMR-assisted one, with several alternatives each. Our results demonstrate that using OMR remarkably reduces users’ effort, even when its performance is far optimal, compared to the fully manual option. © 2021 Proceedings of the 22nd International Conference on Music Information Retrieval, ISMIR 2021. All Rights Reserved.

关键词： Music

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The disinformation battle: Linguistics and artificial intelligence join to beat it

The disinformation battle: Linguistics and artificial intell...

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2020 Doctoral Symposium on Natural Language Processing from the PLN.net Network, PLNnet-DS-2020

作者： Jover, Alba Bonet Department of Software and Computing Systems University of Alicante Spain

At present, the era of digitalisation has led to the era of disinformation by witnessing a peak of the spreading of fake news that are disseminated in order to get profit. Like everything, fake news has an Achilles’ heel and it could be language. The linguistic structure as well as the expression of emotions through language could be key in detecting deception. The modelling of a language of deception typical of fake news and its later automation through machine learning would allow to take a further step towards the fight against disinformation. Copyright © 2020 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0) CEUR Workshop Proceedings (***)

关键词： Modeling languages

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Physical modeling of data warehouses using UML

Physical modeling of data warehouses using UML

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DOLAP 2004: Proceedings of the Seventh ACM International Workshop on Data Warehousing and OLAP

作者： Luján-Mora, Sergio Trujillo, Juan Department of Software and Computing Systems University of Alicante Spain

During the few last years, several approaches have been proposed to model different aspects of a Data Warehouse (DW), such as the conceptual model of the DW, the design of the ETL (Extraction, Transformation, Loading) processes, the derivation of the DW models from the enterprise data models, etc. At the end, a DW has to be deployed to a database environment and that takes many decisions of a physical nature. However, few efforts have been dedicated to the modeling of the physical design (i.e. the physical structures that will host data together with their corresponding implementations) of a DW from the early stages of a DW project. From our previously presented DW engineering process, in this paper we present our proposal for the modeling of the physical design of DWs by using the component diagrams and deployment diagrams of the Unified Modeling Language (UML). Our approach allows the designer to anticipate important physical design decisions that may reduce the overall development time of a DW such as replicating dimension tables, vertical and horizontal partitioning of a fact table, the use of particular servers for certain ETL processes and so on. Moreover, our approach allows the designer to cover all main design phases of DWs, from the conceptual modeling phase until the final implementation, as we show with an example in this paper. Copyright 2004 ACM.

关键词： Data warehouses

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Semi-automatic annotation proposal for increasing a fake news dataset in Spanish

Semi-automatic annotation proposal for increasing a fake new...

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2021 Doctoral Symposium on Natural Language Processing from the PLN.net Network, PLNnet-DS-2021

作者： Bonet-Jover, Alba Department of Software and Computing Systems University of Alicante Spain

The digital era has become an ally of fake news, since it has increased the spread and amount of false information. Fake news is a global problem that causes disorder and generates fear. This phenomenon must be attacked in the same environment in which it is generated: in the digital environment. This paper presents the current state of my doctoral thesis which focuses on the linguistic modelling applied to the automatic detection of fake news through Natural Language Processing (NLP). In order to study the linguistic characteristics of fake news and to create computational models that automate its detection, labelled datasets are needed, but this is a costly task that requires time and expertise. A fake news dataset and an annotation guide were created ad hoc in a previous work to analyse all the parts and elements of a news item. However, after creating and training our system, we realised that the time spent was not proportional to the low annotated data obtained. The need of creating a larger corpus to train and test our hypothesis has led us to think about a way of increasing our corpus without spending so much time. For that purpose, a semi-automatic annotation is proposed for reducing time while increasing speed and quantity of the examples annotated. This proposal, besides allowing us to make progress in our research, may facilitate the creation of datasets, which are essential in NLP research. © 2021 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Linguistics

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A NEURAL APPROACH FOR FULL-PAGE OPTICAL MUSIC RECOGNITION OF MENSURAL DOCUMENTS 21

A NEURAL APPROACH FOR FULL-PAGE OPTICAL MUSIC RECOGNITION OF...

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21st International Society for Music Information Retrieval Conference, ISMIR 2020

作者： Castellanos, Francisco J. Calvo-Zaragoza, Jorge Inesta, Jose M. Department of Software and Computing Systems University of Alicante Spain

ISBN: (纸本)9780981353708

The digitization of the content within musical manuscripts allows the possibility of preserving, disseminating, and exploiting that cultural heritage. The automation of this process has been object of study for a long time in the field of Optical Music Recognition (OMR), with a wide variety of proposed solutions. Currently, there is a tendency to use machine learning strategies based on neural networks because of their high performance and flexibility to adapt to different scenarios by changing only the training data. However, most of the recent literature addresses only specific parts of the traditional OMR workflow such as music object detection or symbol classification. In this paper, we progress one step further by proposing a full-page OMR system for Mensural notation scores that consists of simply two processes, which are enough to extract the symbolic music information from a full page. More precisely, our pipeline uses Selectional Auto-Encoders to extract single staff regions, combined with end-to-end staff-level recognition based on Convolutional Recurrent Neural Networks for retrieving the music notation. The results confirm the adequacy of our method, reporting a successful behavior on two Mensural collections (CAPITAN and SEILS datasets) with a straightforward implementation. © F.J. Castellanos, J. Calvo-Zaragoza and J.M. Iñesta.

关键词： Music

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Exploring the Relationship between News Reliability and Violent Comments in Digital Media 40

Exploring the Relationship between News Reliability and Viol...

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40th Annual Conference of the Spanish Association for Natural Language Processing, SEPLN-P 2024

作者： Botella-Gil, Beatriz Bonet-Jover, Alba Sepúlveda-Torres, Robiert Martínez-Barco, Patricio Saquete, Estela Department of Software and Computing Systems University of Alicante Spain

Natural Language Processing (NLP) has become an essential tool for the automatic detection of violent language and unreliable information. The misuse of Information and Communication Technologies (ICTs) fosters the generation of disinformation and digital violence, thus polarising society. Furthermore, the lack of reliable, neutral and accurate language when presenting news can trigger an increase in negative and violent users’ reactions. It is necessary to find a linkage between disinformation and violent discourse in order to moderate online content, facilitate early detection of both phenomena and ensure healthy online behaviour. This research uses NLP techniques to explore the reliability of news headlines and their correlation with violent language generated in comments by users. In addition, the generation of a novel resource annotated in Spanish is created to jointly address the automatic detection of violent language and reliability. © 2024 Copyright for this paper by its authors.

关键词： Data analysis Natural Language Processing Reliability detection Violent language

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EmotiBlog: A finer-grained and more precise learning of subjectivity expression models

EmotiBlog: A finer-grained and more precise learning of subj...

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4th Linguistic Annotation Workshop, LAW 2010

作者： Boldrini, Ester Balahur, Alexandra Martínez-Barco, Patricio Montoyo, Andrés Department of Software and Computing Systems University of Alicante Spain

ISBN: (纸本)1932432728

The exponential growth of the subjective information in the framework of the Web 2.0 has led to the need to create Natural Language Processing tools able to analyse and process such data for multiple practical applications. They require training on specifically annotated corpora, whose level of detail must be fine enough to capture the phenomena involved. This paper presents EmotiBlog - a fine-grained annotation scheme for subjectivity. We show the manner in which it is built and demonstrate the benefits it brings to the systems using it for training, through the experiments we carried out on opinion mining and emotion detection. We employ corpora of different textual genres -a set of annotated reported speech extracted from news articles, the set of news titles annotated with polarity and emotion from the SemEval 2007 (Task 14) and ISEAR, a corpus of real-life self-expressed emotion. We also show how the model built from the EmotiBlog annotations can be enhanced with external resources. The results demonstrate that EmotiBlog, through its structure and annotation paradigm, offers high quality training data for systems dealing both with opinion mining, as well as emotion detection. © 2010 Association for Computational Linguistics.

关键词： Sentiment analysis

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Lexical ambiguity in cross-language image retrieval: A preliminary analysis

Lexical ambiguity in cross-language image retrieval: A preli...

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2009 Cross Language Evaluation Forum Workshop, CLEF 2009, co-located with the 13th European Conference on Digital Libraries, ECDL 2009

作者： Navarro-Colorado, Borja Puchol-Blasco, Marcel Terol, Rafael M. Vázquez, Sonia Lloret, Elena Department of Software and Computing Systems University of Alicante Spain

In this paper we calculate and analyse the lexical ambiguity of queries in a cross lingual Image Retrieval (Flickling) and compare it with the results obtained by users. We want to know to what extent the lexical ambiguity of a query influences the correct localization of an image in a multilingual framework. With this, our final objective is to determine the necessity of Word Sense Disambiguation systems in Information Retrieval tasks, according to user behaviour. The results show that users really deal with lexical ambiguity: in general terms, users find the correct image with low ambiguity queries.

关键词： Image analysis

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OpAL: Applying opinion mining techniques for the disambiguation of sentiment ambiguous adjectives in SemEval-2 task 18 5

OpAL: Applying opinion mining techniques for the disambiguat...

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5th International Workshop on Semantic Evaluation, SemEval 2010

作者： Balahur, Alexandra Montoyo, Andrés University of Alicante Department of Software and Computing Systems Spain

ISBN: (纸本)1932432701

The task of extracting the opinion expressed in text is challenging due to different reasons. One of them is that the same word (in particular, adjectives) can have different polarities depending on the context. This paper presents the experiments carried out by the OpAL team for the participation in the SemEval 2010 Task 18 - Disambiguation of Sentiment Ambiguous Adjectives. Our approach is based on three different strategies: a) the evaluation of the polarity of the whole context using an opinion mining system;b) the assessment of the polarity of the local context, given by the combinations between the closest nouns and the adjective to be classified;c) rules aiming at refining the local semantics through the spotting of modifiers. The final decision for classification is taken according to the output of the majority of these three approaches. The method used yielded good results, the OpAL system run ranking fifth among 16 in micro accuracy and sixth in macro accuracy. © 2010 Association for Computational Linguistics.

关键词： Sentiment analysis

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