Predicting Active Users' Personality Based on Micro-Blogging Behaviors

Li, Lin; Li, Ang; Hao, Bibo; Guan, Zengda; Zhu, Tingshao

doi:10.1371/journal.pone.0084997

Cited by 113 publications

(92 citation statements)

References 28 publications

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“…First, the personality characteristics extracted using other information such as thoughts and writings of people in the social networks (Qiu et al 2012;L. Li et al 2014) can be considered in finding the influential nodes.…”

Section: Resultsmentioning

confidence: 99%

Using Estimated Personality of Social Network Members for Finding Influential Nodes in Viral Marketing

Amnieh

Kaedi

2015

Cybernetics and Systems

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Sending promotional messages to a few numbers of users in a social network can propagate a product through word of mouth. However, choosing users that receive promotional messages, in order to maximize propagation, is a considerable issue. These recipients are named ''influential nodes.'' To recognize influential nodes, according to the literature, criteria such as the relationships of network members or information shared by each member on a social network have been used. One of the effective factors in diffusion of messages is the personality characteristics of members. As far as we know, although this issue is considerable, so far it has not been applied in the previous studies. In this article, using the graph structure of social networks, two personality characteristics, openness and extroversion, are estimated for network members. Next, these two estimated characteristics together with other characteristics of social networks, are considered as the criteria of choosing influential nodes. To implement this process, the real coded genetic algorithm is used. The proposed method has been evaluated on a dataset including 1000 members of Twitter. Our results indicate that using the proposed method, compared with simple heuristic methods, can improve performance up to 37%.

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Section: Resultsmentioning

confidence: 99%

Using Estimated Personality of Social Network Members for Finding Influential Nodes in Viral Marketing

Amnieh

Kaedi

2015

Cybernetics and Systems

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“…Because some Weibo users are inactive users, and thus not likely to share their attitudes on the internet, this study only focused on active users. In a previous research on Weibo (Li, Li, Hao, Guan, & Zhu, ), researchers found that the distribution of all individual users' total number of posts (136.65 ± 788.87) and average number of daily posts (2.84 ± 2.57). Therefore, in this study, active users were selected based on the following criteria: (a) at least 532 published Weibo posts (136.65 + 0.5 × 788.87 ≈ 532); (b) average number of daily posts ranged from 2.84 (the mean value of all individual users' average number of daily posts) to 40 (a threshold for excluding extreme users, like movie or sports stars, who might update Weibo posts for business purposes).…”

Section: Methodsmentioning

confidence: 96%

Online detection of public attitudes towards China's second‐child policy: A linguistic analysis of social media responses

Jiao²,

Liu

2019

Human Behav and Emerg Tech

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China has relaxed its family planning policy to allow all married couples to have a second child. To ensure a smooth implementation of the new policy (second‐child policy), an efficient detection of public attitudes is necessary. However, traditional methods fail to meet the requirement. This paper aims to examine social media responses, and then uses of linguistic analysis methods to build computational models for automatic detection of attitudinal expressions in social media posts. In this study, a total of 17,305 Sina Weibo posts with keywords were collected and analyzed. First, a content analysis was performed on collected posts to determine whether each of them reflected positive, neutral, or negative attitudes. Second, a series of linguistic features were obtained from each post. Third, based on selected linguistic features, decision tree models were built for differentiating among posts indicating different types of attitudes (positive, neutral, and negative). Results showed that 22.30% of analyzed posts indicated negative attitudes. 62.88% of relevant posts reflected a negative desire for bearing a second child. “Cost and burden” was recognized as a major barrier to the birth of a second child (56.55%). The classification accuracy of decision tree models ranged from 71.6 to 74.4%. This paper supports the need for improving public attitudes towards the second‐child policy, and confirms that the use of linguistic analysis method can add to the validity of online detection of public attitudes towards significant social events.

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“…A personality prediction model trained by machine learning algorithms was used (L. Li et al, ). The training data of the prediction model was the posts from 547 active Chinese Sina Weibo users and their self‐rated personality assessed by 44‐item Big Five Inventory (BFI‐44).…”

Section: Methodsmentioning

confidence: 99%

“…We collected counselors' gender, therapeutic orientation, working time by crawling “Yi Psychology,” and computed their personality traits by ecological recognition technology. Then we used SPSS.19 to compare counselors' personality with the norm group, which were evaluated on the basis of one million microblog users' tweets (L. Li et al, ). We also explored the association of gender, therapeutic orientation, working time, and personality.…”

Section: Methodsmentioning

confidence: 99%

Psychological counselors' self: An ecological recognition of Big Five personality traits based on column blogs in China

Wang

et al. 2019

Human Behav and Emerg Tech

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There is a huge demand of psychological counseling in China, given the growing pains along with dramatic social changes. However, it remains unclear whether psychological counselors hold special psychological qualities as compared to the general population, especially when it is hard to assess psychological professionals' personality using self‐reported methods. Based on the ecological recognition technology, the present research is to explore psychological counselors' personality traits, and to examine the possible effect of gender, therapeutic orientation, and years of experience on personality. One hundred and thirty‐one counselors' introduction and articles on the “Yi Psychology” were collected to analyze their personality using Big Five personality prediction model. The results revealed that psychological counselors showed a higher level of agreeableness, conscientiousness, and openness, but lower extraversion and neuroticism, as compared to norm groups. In addition, there was significant relationship of the counselors' personality to gender and years of experience, but not to their therapeutic orientation. Taken together, the current findings demonstrate the different profile of personality traits among Chinese psychological counselors, compared with norm group. The applications for clinical trainings and selection are discussed.

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Predicting Active Users' Personality Based on Micro-Blogging Behaviors

Cited by 113 publications

References 28 publications

Using Estimated Personality of Social Network Members for Finding Influential Nodes in Viral Marketing

Using Estimated Personality of Social Network Members for Finding Influential Nodes in Viral Marketing

Online detection of public attitudes towards China's second‐child policy: A linguistic analysis of social media responses

Psychological counselors' self: An ecological recognition of Big Five personality traits based on column blogs in China

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