Anonymous Real-Time Analytics Monitoring Solution for Decision Making Supported by Sentiment Analysis

Júnior, Gildásio Antonio de Oliveira; Albuquerque, Robson de Oliveira; Andrade, César Augusto Borges de; Sousa, Rafael T. de; Orozco, Ana Lucila Sandoval; Villalba, Luis Javier García

doi:10.3390/s20164557

Cited by 12 publications

(4 citation statements)

References 36 publications

(58 reference statements)

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“…De Oliveira et al [4] cited an architecture designed to monitor and perform anonymous real-time searches in tweets to generate information allowing sentiment analysis. These results show, data extraction from SMN gives information in real-time and they measure sentiment analysis at a low cost of implementation.…”

Section: Related Workmentioning

confidence: 99%

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Real-Time AI-Based Informational Decision-Making Support System Utilizing Dynamic Text Sources

Islam

Chang

2021

Applied Sciences

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Unstructured data from the internet constitute large sources of information, which need to be formatted in a user-friendly way. This research develops a model that classifies unstructured data from data mining into labeled data, and builds an informational and decision-making support system (DMSS). We often have assortments of information collected by mining data from various sources, where the key challenge is to extract valuable information. We observe substantial classification accuracy enhancement for our datasets with both machine learning and deep learning algorithms. The highest classification accuracy (99% in training, 96% in testing) was achieved from a Covid corpus which is processed by using a long short-term memory (LSTM). Furthermore, we conducted tests on large datasets relevant to the Disaster corpus, with an LSTM classification accuracy of 98%. In addition, random forest (RF), a machine learning algorithm, provides a reasonable 84% accuracy. This research’s main objective is to increase the application’s robustness by integrating intelligence into the developed DMSS, which provides insight into the user’s intent, despite dealing with a noisy dataset. Our designed model selects the random forest and stochastic gradient descent (SGD) algorithms’ F1 score, where the RF method outperforms by improving accuracy by 2% (to 83% from 81%) compared with a conventional method.

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Section: Related Workmentioning

confidence: 99%

“…De Oliveira et al [4] mention anonymous real-time data to generate information which allows sentiment analysis on a given subject and Gajjala et al [5] cite classification for sentiment analysis. Damaschk et al [6] analyzed multiclass text classification on noisy data.…”

Section: Introductionmentioning

confidence: 99%

Real-Time AI-Based Informational Decision-Making Support System Utilizing Dynamic Text Sources

Islam

Chang

2021

Applied Sciences

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“…The use of temporal activity as a behavioural variable was shown to be effective in monitoring fish in real time and remotely, with the potential to alert managers to environmental changes that need attention (Burnett et al, 2020(Burnett et al, , 2021. The use of real-time data collected remotely generates large datasets that need to be analysed in real time to speed up the adaptive management process and rapidly respond to changes in the environment (Burnett et al, 2020;De Oliveira Júnior et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Detecting changes in fish behaviour in real time to alert managers to thresholds of potential concern

Burnett,

Süßle,

Saayman

et al. 2023

River Research & Apps

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Fish behaviour is one biological organisational level regularly used to assess the state of freshwater ecosystems and can be monitored using fish telemetry methods. The development of activity sensors incorporated into fish telemetered tags allows for non‐spatial movement to be detected and is increasingly used to understand the energy budgets and response and fine‐scale behaviour of fishes. In addition, detecting tagged fish remotely and in real time highlights the need to process fish activity data in near real time to make it relevant to managers in the water resource sector. Our study on Labeobarbus natalensis, a cyprinid, in the uMngeni River in KwaZulu‐Natal, South Africa, adapted and then tested the exponentially weighted moving average (EWMA), as developed for financial predictive modelling, using activity data from fish. To determine changes in behaviour, we compared the EWMA‐predicted fish behaviour against the present fish behaviour. We showed that the EWMA could adequately detect changes in behaviour on both individual and population levels. Changes in behaviour are potentially indicative of a change in environmental conditions and thus were developed into management alerts. We conducted further analyses using generalised additive mixed models (GAMM) to determine the relationship between fish activity and the environmental data collected. The GAMMs helped determine the potential drivers for changes in behaviour where the EWMA could detect these in real time. Detecting changes in behaviour in real time as a result of environmental variables can identify thresholds of potential concern influencing management decisions and allow managers to respond, contributing to improving effective freshwater management.

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“…There are also some text mining methods based on other languages, such as Arabic [22]. However, how to match the emotional tendency of Chinese text needs to be studied [5,[23][24][25][26].…”

Section: Introductionmentioning

confidence: 99%

Design Demand Trend Acquisition Method Based on Short Text Mining of User Comments in Shopping Websites

Xiong

Yan

Yao³

et al. 2022

Information

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In order to facilitate designers to explore the market demand trend of laptops and to establish a better “network users-market feedback mechanism”, we propose a design and research method of a short text mining tool based on the K-means clustering algorithm and Kano mode. An improved short text clustering algorithm is used to extract the design elements of laptops. Based on the traditional questionnaire, we extract the user’s attention factors, score the emotional tendency, and analyze the user’s needs based on the Kano model. Then, we select 10 laptops, process them by the improved algorithm, cluster the evaluation words and quantify the emotional orientation matching. Based on the obtained data, we design a visual interaction logic and usability test. These prove that the proposed method is feasible and effective.

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Anonymous Real-Time Analytics Monitoring Solution for Decision Making Supported by Sentiment Analysis

Cited by 12 publications

References 36 publications

Real-Time AI-Based Informational Decision-Making Support System Utilizing Dynamic Text Sources

Real-Time AI-Based Informational Decision-Making Support System Utilizing Dynamic Text Sources

Detecting changes in fish behaviour in real time to alert managers to thresholds of potential concern

Design Demand Trend Acquisition Method Based on Short Text Mining of User Comments in Shopping Websites

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