Topic research in fuzzy domain: Based on LDA topic modelling

Yu, Dejian; Fang, Anran; Xu, Zeshui

doi:10.1016/j.ins.2023.119600

Cited by 16 publications

(3 citation statements)

References 42 publications

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“…However, a qualitative researcher with knowledge of the subject matter and descriptions might fulfil this task if prompted by the study question. The topic modelling procedure enabled us to methodically train the algorithm to characterize groups of words, particularly those critical in our research (Asmussen & Møller, 2019;Yu et al, 2023). After completing the quantitative analysis, the study examined the subjects and identified words related to students' emotions to capture the fundamental aspects of human experiences.…”

Section: Methodsmentioning

confidence: 99%

How Can We Better Comprehend the Disposition of Elementary School Students towards Advanced Mathematical Thinking?

Nadya Dewinda Agustin,

Mohamad Syarif Sumantri,

Arita Marini

2024

JERE

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Conventional mathematics teaching methods emphasize speed and accuracy, creating unnecessary pressure and often inaccurately measuring children's achievements. This research aims to build a framework, systematically examine students' affective areas, especially mathematical dispositions, and analyze the urgency of Advanced Mathematical Thinking (AMT). This research is a comprehensive investigative or exploratory mixed methods research using data triangulation. The subjects involved in this research were 80 elementary school students. The data collection method used was a questionnaire. In addition, this study combined open-ended questions and random narratives that captured participants' perspectives on mathematics learning. The data analysis technique uses qualitative and quantitative descriptive analysis. The research results show that teachers must consider students' various cognitive, emotional and psychomotor capacities and constraints during the educational process. This can be done using appropriate learning activities and methodologies, such as individual assignments and exploratory learning that adapt to students' abilities. Additionally, using narrative-based summative assessments can be an appropriate approach for educators to identify and analyze the specific needs of their students. This research implies the importance of considering students' psychological and emotional factors in designing effective mathematics learning strategies.

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Section: Methodsmentioning

confidence: 99%

How Can We Better Comprehend the Disposition of Elementary School Students towards Advanced Mathematical Thinking?

Nadya Dewinda Agustin,

Mohamad Syarif Sumantri,

Arita Marini

2024

JERE

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“…Zou et al [31] used LDA to extract 26 main research topics from 13,976 abstracts of Chinese policy research papers in the Web of Science (WOS), aiming to identify research topics on China's energy transition policy and predict future research trends. Yu et al [32] used LDA to extract ten latent key scientific topics from a dataset containing 33,957 articles, providing a comprehensive overview of fuzzy research over several decades. Wahid et al [33] argued that social media text data can be utilized for disaster management.…”

Section: Ldamentioning

confidence: 99%

Developing the NLP-QFD Model to Discover Key Success Factors of Short Videos on Social Media

Wu,

Jeng,

Chen

et al. 2024

Applied Sciences

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In the transition from television to mobile devices, short videos have emerged as the primary content format, possessing tremendous potential in various fields such as marketing, promotion, education, advertising, and so on. However, from the available literature, there is a lack of studies investigating the elements necessary for the success of short videos, specifically regarding what factors need to be considered during production to increase viewership. Therefore, this study proposed the NLP-QFD model, integrating Natural Language Processing (NLP), Latent Dirichlet Allocation (LDA), and Quality Function Deployment (QFD) methods. Real short videos from mainstream Western media (CNN) and regional media (Middle East Eye) will be employed as case studies. In addition to analyzing the content of short videos and audiences’ reviews, we will utilize the NLP-QFD model to identify the key success factors (KSFs) of short videos, providing guidance for future short video creators, especially for small-scale businesses, to produce successful short videos and expand their influence through social media. The results indicate that the success factors for short videos include the movie title, promotion, reviews, and social media. For large enterprises, endorsements by famous individuals are crucial, while music and shooting are key elements for the success of short videos for small businesses.

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“…For instance, a study shows that modeling with Latent Dirichlet Allocation (LDA) generates an 18% increase in clicks and a 10% increase in conversions 8) . LDA can infer hidden implicit information from unstructured text data and explore potential topics contained therein 9) . LDA has been used widely to explore topics in various fields, including opinion analysis from consumer reviews of hotels and ride-hailing service providers 10,11) .…”

Section: Introductionmentioning

confidence: 99%

Topic-Based Segmentation in Email Marketing

Surjandari,

Harvey P. Gunawijaya,

Angella Natalia Ghea Puspita

2024

Evergreen

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Email is one of the most common marketing channels businesses use to reach potential customers and advertise their products or services. To maintain the relevance of email messages and the performance of email marketing, personalization, or information from everyone is usually needed. This personalization is often derived from transactional data that reflects the behavior and interests of each customer. However, not all industries have enough transactional data for each of their customers. The challenge is how to use non-transactional data to discover customer interests and preferences. This study proposes to model customer preferences and build customer segmentation in email marketing based on topics and historical email interactions with customers. Biterm Topic Model (BTM) is used in this study for topic modeling because it is suitable for short texts such as email titles. Then segmentation is built based on the generated topics and customer email interaction history. Topic-based segmentation can increase the open rate by nearly two times on average. Marketers can use the findings of this study to develop new strategies and achieve higher email marketing performance.

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Topic research in fuzzy domain: Based on LDA topic modelling

Cited by 16 publications

References 42 publications

How Can We Better Comprehend the Disposition of Elementary School Students towards Advanced Mathematical Thinking?

How Can We Better Comprehend the Disposition of Elementary School Students towards Advanced Mathematical Thinking?

Developing the NLP-QFD Model to Discover Key Success Factors of Short Videos on Social Media

Topic-Based Segmentation in Email Marketing

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