With the growth of social networking website, social media has become a major platform for marketing, such as social business, political manipulation, influence and brand management, etc. However, social media marketing is very different to traditional marketing. Social media marketing needs to face large number of users and need to repeat same process frequently. It is therefore a very human power consuming task. Under this situation, it is the reason why Robotic Process Automation and Social-bots is now very popular in many social networking websites. However, there are many negative effects when applying social-bots for social marketing. Therefore, more and more researchers are devoting on propose efficient ways to detect social-bots. In this paper, we proposed an approach to detect social-bots by considering the content that users posted as well as the behavior and features when using social networking website. In this approach, we adopt the concept of word embedding and social network embedding. Convolutional neural network is used as the main techniques to train the model for social-bots detection. The experimental results show that the proposed combination approach has better detection accuracy than only social network embedding or word embedding approach as well as it reaches 92% detection accuracy by using our dataset.

Web flow now is a very important success factor for social media marketing and thus more and more approaches for creating high web flow have been proposed in recent years. Automatic content generation (ACG) website is one of the possible approaches which can help to create web flow. In order to achieve the idea of automatic content generation website, web article classification has been considered the most important task. Therefore, we have development an empirical study to test the content labeling and article classification performance, which is based on the technique of BERT neural network. The performance evaluation including accuracy performance and time performance that are important for us to understand the possibility for implementing the ACG website in real environment, especially the possibility when dealing with large amount of data.

In recent years, social media has becoming a battle field, not only for online marketing but also for politic, etc. Such as Facebook, online advertisement is now the main revenue of their company and the main idea is to attract users to particular fans page and to create flow. Flow is king is now the important concept for who want to manage their business online. Thus, in this paper, we intend to develop a website based on the concept of auto-article generation (AAG), which can gather useful information or news from other resources from WWW. The techniques that used for the AAG website including web crawler, cloud storage and computing, content classification, etc. The main idea is to attract users to visit the website and by this to create website flow.

Hot topics analysis is one of the important task for users to organize information from WWW and especially for social networking websites. Therefore, how to design an efficient approach for users to extract those hot topics is very essential. Thus, we proposed a so-called 2-layers keywords extraction approach and three empirical analyses are then be applied to validate the usability and performance of the proposed approach.

It is important to perform teamwork with high organizational justice. When some unfair events happen, it is counterproductive not only to the performance of the organization, but to organizational efficacy as well. Presses are time-conscious organizations, but they have to face the difficulty of resource distribution. The main purpose of this study is to examine organizational justice in presses. Because presses are so different from other organizations, there must be some kinds of important elements composing their organizational justice. In the procedure of news gathering, reporters always have to face the uncertainty of those events. If presses emphasize too much on the equity of distribution, it is possible that they may miss the deadline, or even lose the news. So presses seem to need another kind of evaluation to appraise their organizational justice. This paper would focus on the campus media, finding how students perform when they face the assignments of news gathering, and what strategies to do justice in this media could affect students' self-efficacy.