Forecasting popularity of news article by title analyzing with BN-LSTM network

Voronov, Anton; Shen, Yao; Mondal, Pritom Kumar

doi:10.1145/3335656.3335679

Cited by 7 publications

(2 citation statements)

References 18 publications

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“…People not only accept more sources and forms of information in the smart media era, but also make use of new technologies such as social media for emotional resonance and cultural interaction. Various new media platforms not only provide a wide space for people to communicate, but also allow them to learn more about different ideas and cultures [6].…”

Section: People's Values In the Age Of Smart Media Have Socializationmentioning

confidence: 99%

Algorithm Model of People’s Value Identification Strategy in Intelligent Media

Liu,

et al. 2023

Fuzzy Systems and Data Mining IX

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In the age of smart media, information technology is highly developed. This has profoundly changed the way people acquire and disseminate information. In the smart media era, technology has a greater impact on people’s value identity. People are the backbone of the future society, and their ideology and values are directly related to the future direction and trend of society. Based on the general environment of the smart media era, this study will analyze the people’s value expressions of a social event on media platforms through the actual testing and verification of PCA algorithm and TF-IDF algorithm. It will classify the main component values, and calculate the TF-IDF values of the people’s value expressions. So, it can target the people with different mainstream values to conduct guided intelligent story narratives and ultimately improve the people’s values identity.

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Section: People's Values In the Age Of Smart Media Have Socializationmentioning

confidence: 99%

Algorithm Model of People’s Value Identification Strategy in Intelligent Media

Liu,

et al. 2023

Fuzzy Systems and Data Mining IX

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“…They found that users are more likely to click on low-quality articles because of their high title persuasion. Voronov et al [16] developed a language-independent model with an Online Machine Learning approach. Researchers trained and evaluated models on Russian and Chinese articles considering different text preprocessing methods according to these languages' morphology and syntax.…”

Section: Related Workmentioning

confidence: 99%

Prediction of News Popularity via Keywords Extraction and Trends Tracking

Pugachev

Voronov²,

Makarov

2021

Communications in Computer and Information Science

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In the last years, news agencies have become more influential in various social groups. At the same time, the media industry starts to monetize online distributed articles with contextual advertising. However, the efficiency of online marketing highly depends on the popularity of news articles. In our work, we present an alternative and effective way for article popularity forecasting with two-step approach: article keywords extraction and keywords-based article popularity prediction. We show the benefits of this technique and compare with widely used methods, such as Text Embeddings and BERT-based methods. Moreover, the work provides an architecture of the model for dynamic keyword tracking trained on the newest dataset of Russian news articles with more than 280k articles and 22k keywords for the popularity of forecasting purposes.

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A Novel Approach to Determining the Quality of News Headlines

Omidvar

Pourmodheji

et al. 2021

Studies in Computational Intelligence

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Forecasting popularity of news article by title analyzing with BN-LSTM network

Cited by 7 publications

References 18 publications

Algorithm Model of People’s Value Identification Strategy in Intelligent Media

Algorithm Model of People’s Value Identification Strategy in Intelligent Media

Prediction of News Popularity via Keywords Extraction and Trends Tracking

A Novel Approach to Determining the Quality of News Headlines

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