Social networks analysis based on topic modeling

Nguyen, Muon; Ho, Thanh; Do, Phuc

doi:10.1109/rivf.2013.6719878

Cited by 9 publications

(4 citation statements)

References 2 publications

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“…Trong đó, thời gian qua mô hình chủ đề 6 cũng được nhiều tác giả nghiên cứu và thực nghiệm trên tập dữ liệu là các bình luận của khách hàng để lại trên các kênh tiếp nhận phản hồi trực tuyến. Các nghiên cứu này liên quan đến các lĩnh vực như y sinh, giáo dục, nhà ở, mạng xã hội và bán hàng trực tuyến [7][8][9][10][11] . Nhìn chung, nội dung trao đổi của người dùng rất đa dạng phong phú; do đó, đối với các nhà phân tích khi đã khám phá ra các chủ đề nghĩa là khám phá được các thông tin quan trọng, cũng như nắm bắt được thói quen, hành vi của người dùng.…”

Section: Giới Thiệuunclassified

“…Nhìn chung, nội dung trao đổi của người dùng rất đa dạng phong phú; do đó, đối với các nhà phân tích khi đã khám phá ra các chủ đề nghĩa là khám phá được các thông tin quan trọng, cũng như nắm bắt được thói quen, hành vi của người dùng. Tuy nhiên, đối với tính chất của mạng trực tuyến thì chủ đề của nội dung thông điệp trao đổi chưa được tạo trước hay nói cách khác chủ đề được trao đổi trên diễn đàn mạng là tiềm ẩn 10 . Chính vì vậy, việc khám phá chủ đề và hiểu được nội dung thông điệp trao đổi của khách hàng là một thách thức lớn và là bài toán khó 5,9…”

Section: Giới Thiệuunclassified

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Topic modeling for analyzing online reviews in hotel sector

Thanh

2020

Sci. Tech. Dev. J. Econ. Law. Manag.

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Recently, with the growth of technology and the Internet, customers can easily create their opinions and feedbacks about products and services of hotels on websites or social media. This information is stored in textual form, and is a huge source of data to explore. In order to continue developing to meet customers' needs, businesses need to gain customers' insights that customers discuss and concern. In this study, we firstly collected a corpus of 26,482 customer comments and reviews written in English from some e-commerce websites in the hospitality industry. After preprocessing the collected data, our team conducted experiments on this corpus and chose the best number of topics (K) by Coherence Score measurements as input parameters for the model. Finally, experiment on the corpus according to the Latent Dirichlet Allocation (LDA) model with K coefficient to explore the topic. The model results found hidden topics with the corresponding list of keywords, reflecting the issues that customers are interested in. Applying empirical results from the model will support decision making to improve products and services in business as well as in the management and development of businesses in the hotel sector.

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Section: Giới Thiệuunclassified

Topic modeling for analyzing online reviews in hotel sector

Thanh

2020

Sci. Tech. Dev. J. Econ. Law. Manag.

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“…Assuming a Dirichlet prior, LDA models learn probability distributions of words as latent topics in a corpus. In emails, LDA models have been used for learn-ing summary keywords , analyzing how topics change over time (Wang and Mc-Callum, 2006), understanding entity relations (Balasubramanyan and Cohen, 2011), analyzing communication networks (Nguyen et al, 2013), for authorship attribution (Seroussi et al, 2012), and discovering topics associated with authors (McCallum et al, 2005).…”

Section: Generative Models For Emailsmentioning

confidence: 99%

Activity Modeling in Email

Qadir

Gamon

Pantel

et al. 2016

Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Langua

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We introduce a latent activity model for workplace emails, positing that communication at work is purposeful and organized by activities. We pose the problem as probabilistic inference in graphical models that jointly capture the interplay between latent activities and the email contexts they govern, such as the recipients, subject and body. The model parameters are learned using maximum likelihood estimation with an expectation maximization algorithm. We present three variants of the model that incorporate the recipients, co-occurrence of the recipients, and email body and subject. We demonstrate the model's effectiveness in an email recipient recommendation task and show that it outperforms a state-of-the-art generative model. Additionally, we show that the activity model can be used to identify email senders who engage in similar activities, resulting in further improvements in recipient recommendation.

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“…In [39] the authors showed usefulness of topic modeling to analysis of groups dynamics in social networks in blogosphere. Another approach using topic modeling along with social network analysis is presented in [40] where authors track topics in time and automatically assign labels for topics.…”

Section: Text Mining In Domain Of Social Network Aggarwal Andmentioning

confidence: 99%

The Comparison of Users Activity on the Example of Polish and American Blogosphere

Zygmunt

Gliwa

2015

Scientific Programming

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Blogs are popular way to express opinions on the Internet. Due to their popularity and their public character blogs attract attention of many researchers. In this paper we compare two national blogospheres (Polish and American) from different angles such as characteristics of messages and interactions, structure of social groups, topics discussed in them, and the influence of real-world events on the behavior of such groups. In our approach we try to combine in advanced manner users activity on both the individual and community level. The comparison reveals some differences and various characters of both portals. Methods for analysis of groups dynamics, users roles, and topics in groups are presented.

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Social networks analysis based on topic modeling

Cited by 9 publications

References 2 publications

Topic modeling for analyzing online reviews in hotel sector

Topic modeling for analyzing online reviews in hotel sector

Activity Modeling in Email

The Comparison of Users Activity on the Example of Polish and American Blogosphere

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