A novel semantic level text classification by combining NLP and Thesaurus concepts

Nagaraj, R.; Thiagarasu, V.

doi:10.9790/0661-16461426

Cited by 5 publications

(2 citation statements)

References 13 publications

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“…6, is one of the text analysis processes. Examples of previous studies on text classification are [41] who proposed a novel approach to classify the text semantically (featured small text classification) using Twitter [42], and also hashtag categories created through contemporary classification employing Twitter [43].…”

Section: A Text Analysismentioning

confidence: 99%

Tracking Dengue on Twitter Using Hybrid Filtration-Polarity and Apache Flume

Ghani¹,

Hamid²,

Ahmad³

et al. 2022

Computer Systems Science and Engineering

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The world health organization (WHO) terms dengue as a serious illness that impacts almost half of the world's population and carries no specific treatment. Early and accurate detection of spread in affected regions can save precious lives. Despite the severity of the disease, a few noticeable works can be found that involve sentiment analysis to mine accurate intuitions from the social media text streams. However, the massive data explosion in recent years has led to difficulties in terms of storing and processing large amounts of data, as reliable mechanisms to gather the data and suitable techniques to extract meaningful insights from the data are required. This research study proposes a sentiment analysis polarity approach for collecting data and extracting relevant information about dengue via Apache Hadoop. The method consists of two main parts: the first part collects data from social media using Apache Flume, while the second part focuses on querying and extracting relevant information via the hybrid filtration-polarity algorithm using Apache Hive. To overcome the noisy and unstructured nature of the data, the process of extracting information is characterized by pre and post-filtration phases. As a result, only with the integration of Flume and Hive with filtration and polarity analysis, can a reliable sentiment analysis technique be offered to collect and process large-scale data from the social network. We introduce how the Apache Hadoop ecosystem -Flume and Hivecan provide a sentiment analysis capability by storing and processing large amounts of data. An important finding of this paper is that developing efficient sentiment analysis applications for detecting diseases can be more reliable through the use of the Hadoop ecosystem components than through the use of normal machines.

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Section: A Text Analysismentioning

confidence: 99%

Tracking Dengue on Twitter Using Hybrid Filtration-Polarity and Apache Flume

Ghani¹,

Hamid²,

Ahmad³

et al. 2022

Computer Systems Science and Engineering

View full text Add to dashboard Cite

show abstract

“…By using text analytics software and analysis models, the generated indices can be stored in a structured database and incorporated in other analyses, such as predictive data mining projects and unsupervised learning methods. In addition, researchers and industrial experts can use text analytics to gain insight into content-specific values, such as sentiment, emotion, intensity, and relevance (Nagaraj et al, 2014). Different techniques are utilized in the text mining area, such as text categorization, text clustering, entity extraction, sentiment analysis, document summary, and entity-relation modeling (Agrawal and Batra, 2013;Mooney et al, 2006).…”

Section: Text Miningmentioning

confidence: 99%