A Scalable Platform to Collect, Store, Visualize and Analyze Big Data in Real- Time

Kshirsagar, Pravin R.; Reddy, Dhoma Harshavardhan; Dhingra, Mallika; Dhabliya, Dharmesh; Gupta, Ankur

doi:10.1109/iciptm57143.2023.10118183

Cited by 12 publications

(4 citation statements)

References 47 publications

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“…With BERT-based models on Twitter, YouTube, Facebook, Amazon, TripAdvisor, Opera, and Personal Healthcare Agent, [45] analyses Italian corpora for sentiment. [65] mines Twitter data for sentiment analysis while [129] suggests using NLP to solve erroneous usergenerated reviews in e-commerce. Furthermore, [145] proposes a Twitter reputation generating method that handles multiple sources.…”

Section: Handling Diverse Data Sourcesmentioning

confidence: 99%

Natural Language Processing for Analyzing Online Customer Reviews: A Survey, Taxonomy, and Open Research Challenges

Malik,

Bilal

2024

Preprint

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In recent years, e-commerce platforms have replaced conventional marketplaces. People are rapidly adopting internet shopping due to the convenience of making purchases from the comfort of their homes. Online review sites allow customers to share their thoughts on products and services. Customers and businesses are increasingly relying on online reviews to assess and improve the quality of products. Existing literature uses Natural language processing (NLP) to analyze customer reviews for different applications. Due to the growing importance of NLP for online customer reviews, this study attempts to provide a taxonomy of NLP applications based on existing literature. This study also examined emerging methods, data sources, and research challenges by reviewing 154 publications from 2013 to 2023 that explore state-of-the-art approaches for diverse applications. Based on existing research, the taxonomy of applications divides literature into five categories: sentiment analysis, review analysis, customer feedback and satisfaction, user profiling, and marketing and reputation management. It is interesting to note that the majority of existing research relies on Amazon user reviews. Additionally, recent research has encouraged the use of advanced techniques like Bidirectional Encoder Representations from Transformers (BERT), Long Short-Term Memory (LSTM), and ensemble classifiers. The rising number of articles published each year indicates increasing interest of researchers and continued growth. This survey additionally addresses open issues, providing future directions in online customer review analysis.

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Section: Handling Diverse Data Sourcesmentioning

confidence: 99%

Natural Language Processing for Analyzing Online Customer Reviews: A Survey, Taxonomy, and Open Research Challenges

Malik,

Bilal

2024

Preprint

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“…9. Cross-Border Greetings: Global Reach: Blockchain can facilitate cross-border greetings and payments, making it easier for people around the world to exchange greetings and value [21][22][23][24][25][26][27][28][29].…”

Section: Loyalty Programs: Blockchain-based Rewardsmentioning

confidence: 99%

Investigating Role of Blockchain in Making your Greetings Valuable

GUPTA,

Gupta

2023

URR

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Current study is mostly focused on the exploration of the role of blockchain technology in enhancing the value of greetings. To accomplish this goal, renowned blockchain-based greetings NFTs from Opensea and Young Parrot have been taken into account. The welcome non-fungible tokens (NFTs) are built upon the Matic and Core blockchain networks. In order to get insight into the key determinants that significantly impact the demand for blockchain-based NFTs used for greetings, a comprehensive survey was undertaken including all facets of this burgeoning phenomenon. Extensive research has been undertaken to enhance comprehension of the determinants that propel the demand for NFTs based on blockchain technology within the domain of greetings. The factors under consideration include the pricing, overall quantity, use case, and popularity of NFTs. A survey was conducted on Twitter, using a sample size of 525 individuals. Based on the findings of the conducted study, it can be deduced that the primary determinant of the value attributed to greetings is their level of popularity. Furthermore, it has been observed that the Love Emogie have a restricted availability. The limited availability of just 43 Love Emojie has contributed to the heightened demand for NFTs owing to their inherent scarcity. However, it is also noted that pricing and use case have a substantial influence.

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“…The research used consumer input to improve corporate strategy and predict customer requirements. Twitter data obtained via the API key was analyzed using NLP techniques, demonstrating their ability to provide organizations with important insights for personalized marketing and organizational benefit [65]. The summary of existing literature on sentiment analysis and opinion mining is given in Table 2.…”

Section: Sentiment Analysis and Opinion Miningmentioning

confidence: 99%

“…With BERT-based models on Twitter, YouTube, Facebook, Amazon, TripAdvisor, Opera, and Personal Healthcare Agent, [45] analyses Italian corpora for sentiment. [65] mines Twitter data for sentiment analysis while [129] suggests using NLP to solve erroneous user-generated reviews in e-commerce. Furthermore, [145] proposes a Twitter reputation generating method that handles multiple sources.…”

Section: Handling Diverse Data Sourcesmentioning

confidence: 99%

Natural Language Processing for Analyzing Online Customer Reviews: A Survey, Taxonomy, and Open Research Challenges

Malik,

Bilal

2023

Preprint

View full text Add to dashboard Cite

In recent years, e-commerce platforms have replaced conventional marketplaces. People are fast adopting online shopping since they can purchase from home. Online review sites allow customers to share their thoughts on products and services. Customers and businesses are increasingly relying on online reviews to assess and improve the quality of products. Existing literature uses Natural language processing (NLP) to analyze customer reviews for different applications. Due to the growing importance of NLP for online customer evaluations, this study attempts to provide a taxonomy of NLP applications based on existing literature. This study also examined emerging methods, data sources, and research challenges. This study covers 154 publications from 2013 to 2023 that explore state-of-the-art approaches for diverse applications. Based on existing research, the taxonomy of applications divides literature into five categories: sentiment analysis, review analysis, customer feedback and satisfaction, user profiling, and marketing and reputation management. It is interesting to note that the bulk of existing research relies on Amazon user reviews. Additionally, recent research has stressed the use of advanced techniques like Bidirectional Encoder Representations from Transformers (BERT), Long Short-Term Memory (LSTM), and ensemble classifiers. The rising number of articles published each year indicates researchers' expanding interest and the field's continued growth. This survey additionally addresses open issues, providing future directions in online customer review analysis.

show abstract

A Scalable Platform to Collect, Store, Visualize and Analyze Big Data in Real- Time

Cited by 12 publications

References 47 publications

Natural Language Processing for Analyzing Online Customer Reviews: A Survey, Taxonomy, and Open Research Challenges

Natural Language Processing for Analyzing Online Customer Reviews: A Survey, Taxonomy, and Open Research Challenges

Investigating Role of Blockchain in Making your Greetings Valuable

Natural Language Processing for Analyzing Online Customer Reviews: A Survey, Taxonomy, and Open Research Challenges

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