Social Media Data-Based Sentiment Analysis of Tourists’ Air Quality Perceptions

Recently, the issue of air quality in South Korea reached an unprecedented level of social concern regarding public health, quality of life, and environmental policies, even as the level of particulate matter less than 10 μm (PM10) showed a decreasing trend. Why have social concerns emerged in recent years, specifically after 2013–2014? This study aims to understand how people perceive air quality apart from the measured levels of airborne pollutants using internet search volume data from Google and NAVER. An empirical model that simulates the air quality perception index (AQPI) is developed by employing the decay theory of forgetting and is trained by PM10, visibility, and internet search volume data. The results show that the memory decay exponent and the accumulation of past memory traces, which represent the weighted sum of past perceived air quality, play key roles in explaining the public’s perception of air quality. A severe haze event with an extremely long duration that occurred in the year 2013–2014 increased public awareness of air quality, acting as a turning point. Before the turning point, AQPI is more influenced by sensory information (visibility) due to the low awareness level, but after the turning point it is more influenced by PM10 and people slowly forget about air quality. The retrospective AQPI analysis under a low level of awareness confirms that perceived air quality is indeed worst in the year 2013–2014. Our results provide a better understanding of public perception of air quality, and will contribute to the creation of more effective regulatory policies. It should be noted, however, that the proposed model is primarily meant to diagnose historic public perception and that more sophisticated models are needed to reliably predict perception of air quality.

As gender may influence thermal and air quality perception in indoor environments, the aim of this study was to analyse gender influence on air movement, air humidity, air quality and thermal perception in office buildings in Southern Brazil. Statistical descriptions, regression analyses and hypothesis tests were performed using data collected from field studies conducted in a fully air-conditioned building and in three mixed-mode buildings. In addition, comfort temperatures were estimated through the Griffiths method. Results showed that females tend to feel colder compared to males. Men and women tended to present higher thermal acceptability and thermal comfort in mixed-mode buildings and in fully air-conditioned buildings, respectively. Weak but significant correlations were obtained between some environmental and subjective variables. In general, comfort temperatures were statistically higher for females (24.2 °C) than for males (23.5 °C). Significant gender differences for thermal perceptions of indoor environments were detected.

Perception of air quality and its health effects, as an topic in public health research Perception of air quality and its health effects, as an topic in public health research Perceived air quality is an important measure for evaluating the health impact and quality of life in studies that have been carried out in the area of public health for years. The aim of this paper is to review and sum up the multidisciplinary knowledge regarding this topic, as well as to outline some main insights presented in the field of risk perception research. The literature on the perception of air pollution risks is structured around the five topics, proposed by the authors. Particular attention is focused on research that explores such issues as: factors influencing the air quality perception, the association between the subjective assessment of air pollutants and their objectively measured levels, the influence that perception of air quality has on human attitudes and activities. The paper concludes by evaluating the relevance of the reviewed knowledge for the future research and the field of public health practice.

A Strategy for Network multi-layer Information Fusion Based on Multimodel in User Emotional Polarity Analysis

Outdoor air pollution and especially particulate matter pollution is a major environmental health issue that raises concerns of scientists and policy makers. This study focuses on air quality perception in relation to particulate matter in order to find potential patterns. Field questionnaire-based surveys were conducted among pedestrians on two central sites in the city of Athens, Greece, during the winter period while particulate matter of 10μm or less in diameter (PM10) were concurrently measured on-site at 1-min resolution. The participants were asked to evaluate the dust and the overall pollution-related air quality based on 5-point bipolar scales. Air quality perception patterns were explored considering PM10 concentration, meteorological and thermal conditions, and subjective variables including gender, age, smoking status, and health status. An effect of PM10 on dust perception was identified, suggesting that dusty air quality conditions are reported more frequently when particulate concentration increases. Health status, exposure time, smoking status, and gender were found to affect air quality perception. Participants experiencing health symptoms, exposed to outdoor conditions for more than 30min, smokers, and females were more likely to report unfavorable air quality conditions. The comparison with the results of a previous study obtained using air pollution station data confirmed the dependence of air quality perception on participants' characteristics and particularly on their health status. Ordinal logistic regression models showed that for pedestrians who were neither smokers nor experiencing health symptoms and were exposed to outdoor conditions for more than 30min, a PM10 concentration around 64μg·m-3 could be a threshold, to perceive dusty air quality conditions.

Applications in the World Wide Web aggregate vast amounts of information from different data sources. The aggregation process is often implemented with Extract, Transform and Load (ETL) processes. Usually ETL processes require information for aggregation available in structured formats, e. g. XML or JSON. In many cases the information is provided in natural language text which makes the application of ETL processes impractical. Due to the fact that information is provided in natural language, Information Extraction (IE) systems have been evolved. They make use of Natural Language Processing (NLP) tools to derive meaning from natural language text. State-of-the-art NLP tools apply Machine Learning methods. These NLP tools perform on newspapers with good quality, but they drop accuracy in other domains. However, to improve the quality for IE systems in specific domains often NLP tools are trained on domain specific text which is a time consuming process. This paper introduces an approach using a Continuous Integration pipeline for organizing and monitoring the annotation process on domain specific corpora.

Background Despite the popularity of low emissions zones (LEZ) across Europe their public acceptability and impact on travel behaviours are scarcely studied. We aimed to explore changes in acceptability, perceptions of air quality, and travel behaviours in a multi-ethnic sample living in Bradford, UK after the implementation of a Clean Air Zone (a type of LEZ). Methods Telephone, in-person and online surveys were conducted one year pre- and one year post implementation. Participants included members of the representative Born in Bradford (BiB) cohort and members of the general public. A repeated cross-sectional analysis explored changes in responses between baseline and follow-up questions using chi-square tests and tests of proportions. Multinomial regressions explored whether socio-demographic variables were associated with changes in attitudes longitudinally. Results A total of 1,949 and 2,085 individuals participated in the baseline and follow-up surveys; 814 participants completed both. Participants were mostly female, aged 35–44. Half were white British, and 30% of Pakistani origin. The majority of participants supported the clean air zone at follow-up (59–64%), although these figures were lower than at baseline (by 4.9% for BiB families and 10.8% for members of the general public). A third indicated high concern about air quality (34–38%). Personal travel behaviours showed little variation pre to post implementation. On the whole, attitudes of those completing both surveys remained stable, and there were no systematic relationships between socio-demographic variables and whether attitudes worsened or became more positive. Conclusion Whilst CAZ support remained high, we observed small decreases in support after the CAZ implementation. As public acceptability is a key facilitator to the success of initiatives such as CAZ, a decrease in public support may threaten their sustainability. Communication about the need for CAZ, and demonstrations of their positive impact will be important to maintain levels of acceptability.

Research on environmental health risks suggests that public perceptions of risk may be greater than quantitative health risk assessments, especially amongst vulnerable groups such as women and immigrants. This study uses the environmental stress and coping framework to examine individual perceptions of air quality amongst Canadian-born and immigrant women in Northeast Hamilton, Ontario, Canada. Furthermore, the study aims to determine the influence of sense of place on local environmental perceptions. Quantitative survey results suggest that Canadian-born residents have a higher absolute value of sense of place than immigrants. Qualitative focus group discussions suggest that, compared to immigrant women, Canadian-born women may be more aware, knowledgeable and concerned about larger-scale air quality issues; however, the tension between economic and environmental needs hinders their sense of control. Bringing the quantitative and qualitative data together suggests that sense of place may inform environmental perceptions.

V članku so predstavljeni rezultati raziskave, ki je z obsežnim anketiranjem v mestu Ljubljana ugotavljala zaznavanje kakovosti zraka, in sicer tako v primerjavi z zaznavanjem drugih okoljevarstvenih področij kot tudi v primerjavi z rezultati monitoringa kakovosti zraka na preučevanem območju. Ugotovitve kažejo, da prebivalci zaznavajo onesnaženost zraka kot glavni okoljski problem v mestu in da prepričanje o slabi kakovosti zraka v Ljubljani ostaja globoko zakoreninjeno kljub njenemu splošnemu izboljšanju.

We present SimpleApprenant, a platform aiming to improve French L2 learners’ knowledge of Multi Word Expressions (MWEs). SimpleApprenant integrates an MWE database annotated with the Common European Framework of Reference for languages (CEFR) level and several Natural Language Processing (NLP) tools: a spelling checker, a parser, and a set of transformation rules. NLP tools and resources are used to build training and writing exercises to improve MWE knowledge and writing skills of French L2 learners. We present the user scenarios, the platform’s architecture, as well as the preliminary evaluation of its NLP tools.

An assessment of perceptions of air quality surrounding the implementation of a traffic-reduction measure in a local urban environment

In the age of knowledge, Natural Language Processing (NLP) express its demand by a huge range of utilization. Previously NLP was dealing with statically data. Contemporary time NLP is doing considerably with the corpus, lexicon database, pattern reorganization. Considering Deep Learning (DL) method recognize artificial Neural Network (NN) to nonlinear process, NLP tools become increasingly accurate and efficient that begin a debacle. Multi-Layer Neural Network obtaining the importance of the NLP for its capability including standard speed and resolute output. Hierarchical designs of data operate recurring processing layers to learn and with this arrangement of DL methods manage several practices. In this paper, this resumed striving to reach a review of the tools and the necessary methodology to present a clear understanding of the association of NLP and DL for truly understand in the training. Efficiency and execution both are improved in NLP by Part of speech tagging (POST), Morphological Analysis, Named Entity Recognition (NER), Semantic Role Labeling (SRL), Syntactic Parsing, and Coreference resolution. Artificial Neural Networks (ANN), Time Delay Neural Networks (TDNN), Recurrent Neural Network (RNN), Convolution Neural Networks (CNN), and Long-Short-Term-Memory (LSTM) dealings among Dense Vector (DV), Windows Approach (WA), and Multitask learning (MTL) as a characteristic of Deep Learning. After statically methods, when DL communicate the influence of NLP, the individual form of the NLP process and DL rule collaboration was started a fundamental connection.

This study addresses the issue of air quality in early modern Czech lands (Bohemia) through an analysis of contemporary texts intended both for scholars and ordinary citizens. From the times of Hippocrates and Galen until the modern period, medicine was based mainly on dietetics, which included the overall lifestyle. Its principle was harmony of human activities as well as the use of what Galen called the sex res non naturales (six non-natural things), where the first field of interest was light and air. Lay scholars, secular authorities, representatives of municipalities, and later also superordinate authorities did not remain impartial and paid close attention to the issue of the relationship of human health and the environment. This study is based on the analysis of anti-plague documents written by doctors and lay scholars, and on official regulations for early modern Bohemia. The contemporary topographies that describe the landscape and air are used as well to identify and clarify the discourse on the importance of good air quality to combat epidemics.

RATIONALE:Medical faculty building architecture and ventilation systems have evolved with advancements in public health, societal needs, and technology. Early 20th-century designs prioritized natural ventilation(NV) through high ceilings and large windows for improved airflow. While more enclosed systems have been adopted in recent decades, NV remains an effective and eco-friendly method for ensuring good indoor air quality (IAQ).Air changes per hour(ACH) during NV are crucial for removing pollutants, microorganisms. IAQ is vital for health and cognitive performance, especially in lecture halls.This study aims to evaluate IAQ with NV in a medical faculty in Ankara, while exploring students’ perceptions and potential health effects. METHODS:This descriptive study was conducted in Faculty of Medicine classrooms in May and June 2024 after obtaining necessary permissions.Seven classrooms with NV were randomly selected, excluding those without windows or requiring mechanical ventilation.Data were collected using calibrated anemometers to measure ACH during lectures, with windows and doors closed initially and open during breaks.Air quality metrics including carbon dioxide(CO2), volatile organic compounds(VOCs), nitrogen oxides(NOx), particulate matter(PM10, PM2.5, PM1), were recorded at one-minute intervals. A survey with 97 students assessed their perceptions of air quality and health effects.Statistical analyses included descriptive statistics, Chi-square or Fisher's exact tests for categorical variables, using SPSS Statistics(IBM, v29), with a significance level set at 0.05. RESULTS:Figure-1A demonstrates the course of CO2, PM1, PM2.5, PM10, VOC and NOx index, during the lecture with doors and windows closed and during breaks with them open.Figure-1B illustrates a measurement taken during the exam process, a common scenario in faculty classrooms, where cognitive functions are crucial.In this case, doors and windows were kept open from the start.Excellent ACH values were achieved in both classrooms with NV.Characteristics and survey responses of the 97 participants are shown in Figure-1C. 73.2% reported no chronic health conditions, while 26.8% had conditions such as allergies(7.1%), asthma(4.1%), anxiety disorders(4.1%). 27.8% of participants reported health issues linked to IAQ, with women reporting more frequently(p=0.044).Maintenance/cleaning issues were significantly associated with these complaints(p=0.048).The most common symptoms included runny nose, sneezing, headache, difficulty concentrating, dry skin, throat irritation, and sleepiness. CONCLUSION:This descriptive study highlights the importance of NV in medical faculty classrooms for improving IAQ.It supports practical, eco-friendly, and cost-effective measures, such as opening windows and doors during breaks.Future policies should enhance air quality standards, implement routine monitoring, and promote NV methods, fostering healthier, more productive learning environments that support public health and well-being in settings with adequate NV resources.

Perceptions about air quality of individuals who work outdoors in the San Joaquin Valley, California