What Prompts Users to Click on News Headlines? A Clickstream Data Analysis of the Effects of News Recency and Popularity

Jiang, Tingting; Guo, Qian; Xu, Yang; Zhao, Yang; Fu, Shiting

doi:10.1007/978-3-030-15742-5_51

Cited by 6 publications

(4 citation statements)

References 20 publications

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“…Textual features have been proven to influence the acceptance of information ( Jiang et al, 2019 ; Liu et al, 2019 ), but they are rarely used in the field of mental health education. In this study, teenager students express a strong preference for textual features.…”

Section: Discussionmentioning

confidence: 99%

“…Szuchewycz et al found that text with clear language, firm tone, emotional color, and specific rhetoric is highly persuasive ( Szuchewycz, 1995 ). Numerous studies have also shown that the length of the text, the placement of certain words and symbols, and the use of numbers increase the impact of a text ( Jiang et al, 2019 ; Pengnate, 2019 ). Why do texts with distinct features have different effects even when they express the same idea?…”

Section: Introductionmentioning

confidence: 99%

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Textual Features and Risk Preference Effects on Mental Health Education Among Teenager Students in Chongqing, China

Jiang

Zhang

Kang³

et al. 2022

Front. Psychol.

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BackgroundMental health is a public health problem of great concern. Previous studies show that textual features and individual psychological characteristics can influence the effect of receiving information.PurposeThis study explores whether textual features influence the persuasiveness of teenager students’ mental health education while considering the influence of risk preference.MethodsFrom November to December 2021, a cross-sectional study was conducted among 1,869 teenager students in grade 7–12 in Chongqing, China. Wilcoxon signed-rank test, multiple logistic regression, and subgroup analysis were used to analyze the data.ResultsAmong the four textual features mentioned in this study, a significant difference was reported in the persuasive effects of information with and without numerical features (p < 0.001), and such information tended to include digital features. The result for the symbolic features (p < 0.001) was consistent with the numerical features. The persuasive effects of positive and negative emotional information significantly differed (p < 0.001), with the former showing a better performance. No significant differences were observed between the persuasive effects of information with and without emotional conflicts (p > 0.05). Combined with those from the risk preference analysis, results showed that the regulatory effect of risk preference was only reflected in emotional conflicts. Students who prefer having no emotional conflict in the text showed the characteristics of risk avoidance, or lower grades, or rural or school accommodation. Most teenager students are also risk averse, especially females (or = 2.223, 95%CI:1.755–2.815) and juniors (or = 1.533, 95%CI: 1.198–1.963).ConclusionThe numbers, symbols, and positive emotions in the text generate an active effect on teenager students receiving mental health education. Students avoiding risk are inclined to read texts without emotional conflicts. The probability of male choosing texts with positive emotional polarity is 33.5% lower than that of female. Female students and those from lower grades also demonstrate a higher inclination to risk avoidance compared with their male and higher grade counterparts. Therefore, educational materials with different text characteristics should be developed for teenager students with varying characteristics.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Textual Features and Risk Preference Effects on Mental Health Education Among Teenager Students in Chongqing, China

Jiang

Zhang

Kang³

et al. 2022

Front. Psychol.

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“…This study followed a general framework of clickstream data analysis which has been successfully applied in the studies of users' information seeking behavior in social library systems and academic library OPAC systems (Jiang, Guo, Xu, Zhao, & Fu, ), and the above data was analyzed at the footprint and movement levels. When a user visits the PTA account, each click causes a movement, the changing of location from one page to another, and leaves a footprint, a mark showing the user's presence on a page.…”

Section: Methodsmentioning

confidence: 99%

A clickstream data analysis of users' behavior on a government WeChat official account

Jiang

Lin

Shangguan

et al. 2019

Proceedings of the Association for Information Science and Tech

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This study took a user‐oriented approach to investigating the effectiveness of a government WeChat official account in terms of service delivery. A transaction log file containing 42,188,760 clickstream records was obtained from an active account and analyzed at the footprint and movement levels. The current clickstream data analysis revealed the underutilization of the services provided by the account, the failure of the three navigational portals, and the poor completion rates of the tasks users performed on the account.

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“…Clickbait is not a new phenomenon (Mormol, 2019), the technique of enticing readers through the use of exaggerated and sensationalistic headlines can be found in tabloid newspapers as far back as the 1980s (Chen et al, 2015). From a journalistic perspective, news headlines have been transformed by digital reporting into elements intended to attract reader attention rather than provide information (Jiang et al, 2019). The use of clickbait techniques seems to be spreading to include mainstream news media and entertainment content (Rony et al, 2017) and has been thrust into the spotlight by the recent proliferation of fake news (Zannettou et al, 2018).…”

Section: Literature Reviewmentioning

confidence: 99%

The Linguistic and Typological Features of Clickbait in Youtube Video Titles

Kemm

2022

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This exploratory study aims to identify which linguistic and typological features commonly associated with clickbait in online news headlines are indicative of clickbait in YouTube video titles. A comparative corpus analysis is conducted to compare YouTube video titles commonly associated with clickbait to titles not associated with clickbait. Results indicate that a majority of the typological and linguistic features associated with clickbait in online news headlines are found to be indicative of clickbait in YouTube video titles. However, the role which each of the features plays seems to differ to that of online news. The findings contribute to the understanding of clickbait in non-news contexts from a linguistics perspective, an area which has been relatively unexplored in the current literature.

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What Prompts Users to Click on News Headlines? A Clickstream Data Analysis of the Effects of News Recency and Popularity

Cited by 6 publications

References 20 publications

Textual Features and Risk Preference Effects on Mental Health Education Among Teenager Students in Chongqing, China

Textual Features and Risk Preference Effects on Mental Health Education Among Teenager Students in Chongqing, China

A clickstream data analysis of users' behavior on a government WeChat official account

The Linguistic and Typological Features of Clickbait in Youtube Video Titles

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