Indicators for the assessment of social resilience in flood-affected communities – A text mining-based methodology

Jacinto, Rita; Reis, Eusébio; Ferrão, João

doi:10.1016/j.scitotenv.2020.140973

Cited by 24 publications

(6 citation statements)

References 53 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…One way to extract text data more naturally is by using the Text Mining technique. Text Mining has invaluable commercial value since it's a simplified and faster way to collect data and can be applied in different areas (57)(58)(59)(60)(61)(62)(63)(64)(65)(66)(67)(68)(69)(70)(71)(72)(73).…”

Section: Discussionmentioning

confidence: 99%

Drug delivery polymers: An Analysis Based on Literature Text Mining

Daher¹,

Souza²,

Carelo³

et al. 2021

BJEDIS

View full text Add to dashboard Cite

Many polymers are used as drug carriers for controlled delivery because of its many advantages. To find the most used polymers for this purpose in recent years, we chose to use Text Mining as an evaluation tool. Text Mining tool was precious in this work to identify the main polymers that contributed to drug delivery, allowing us to draw a map year by year based on correlation analyzes. Firstly, an analysis was made on what was most researched per year, and then what were the most cited polymers. Then the most mentioned polymers were separated and organized to observe which year it was more or less cited. It was found with this work that none of the polymers showed only positive correlations in all years. Besides, polymers did not reveal individual growth in their use over the years. The Text Mining presented here proved to be an efficient and quick way to observe the desired theme and open up possibilities for research in different fields.

show abstract

Section: Discussionmentioning

confidence: 99%

Drug delivery polymers: An Analysis Based on Literature Text Mining

Daher¹,

Souza²,

Carelo³

et al. 2021

BJEDIS

View full text Add to dashboard Cite

show abstract

“…Social or community resilience is a widely used framework to analyze signi cant social issues from migration to environmental changes [4,5,6,7]. Steiner et al [8] present a community resilience framework which is based on the premise that proactive migrant communities that take advantage of community developmental opportunities become more resilient while those that do not engage community resources are less resilient.…”

Section: Mccarthy and Hattawaymentioning

confidence: 99%

Community Resilience and Migration: Using Best Evidence Synthesis to Promote Migrant Welfare

D’Souza

2023

Preprint

View full text Add to dashboard Cite

Community resilience is an important success factor in migration. Many migrants experience behavioral and psychological change due to hardships post-migration. Migrant communities that learn to withstand these hardships are said to be resilient. This paper discusses the different factors that influence migration and the level of community resilience. These factors are: empowerment, social networks, change in the ecological and natural environment and economic factors. By using the best evidence synthesis methodology, this study was able to select the most commonly discussed stressors, practices and desired outcomes. In the thirty-one studies reviewed, the variables that had the highest impact on migrant communities were ranked to help community organizations determine which practices to prioritize in building resilience among migrants. Community actions that back migrant integration, health and well-being, education and support services ranked the highest in this best evidence study. These rankings are important in identifying and prioritizing community developmental opportunities that enhance migrant resilience during the settlement process.

show abstract

“…Sentiment analysis aims to evaluate the emotions, opinions, and evaluations conveyed by the speaker or writer towards a product, service, or person's personality. Some research, especially on products, is preceded by determining the discussion of a product before starting the opinion exploration process [12]. Sentiment analysis is the process of understanding and classifying what is contained in writing using text analysis techniques.…”

Section: Aspect-base Sentiment Analysismentioning

confidence: 99%

Auto Labeling to Increase Aspect-Based Sentiment Analysis Using K-Nearest Neighbors Method

2022

View full text Add to dashboard Cite

Social media platforms generate many opinions, emotions, and views on all public services. Sentiment analysis is used in various institutions, such as universities, the business industry, and politicians. The evaluation process requires some data, both quantitative and qualitative. Researchers only focus on quantitative data but ignore qualitative data. The evaluation process given by students in the form of a review is qualitative data that is not structured, so it cannot use conventional methods. Unstructured data requires analysis as well as labeling. The labeling process of large amounts of data is a waste of time and money. Data labeling requires very high accuracy to avoid errors. Accuracy in data labeling is used for the process of classifying, training, and testing data. This study aims to automate data labeling using the K-Nearest Neighbors algorithm method. This labeling process can improve the accuracy of sentiment analysis. The results of the classification method can classify responses from Twitter users and can be used by universities as material for evaluating and assessing higher education services. The results of using a confusion matrix with 1.409 data obtained an accuracy rate of 79.43% with a value of k=15

show abstract

Indicators for the assessment of social resilience in flood-affected communities – A text mining-based methodology

Cited by 24 publications

References 53 publications

Drug delivery polymers: An Analysis Based on Literature Text Mining

Drug delivery polymers: An Analysis Based on Literature Text Mining

Community Resilience and Migration: Using Best Evidence Synthesis to Promote Migrant Welfare

Auto Labeling to Increase Aspect-Based Sentiment Analysis Using K-Nearest Neighbors Method

Contact Info

Product

Resources

About