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This paper proposes an approach to identify categorical influencers (i.e. influencers is the person who is active in the targeted categories) in social media channels. Categorical influencers are important for media marketing but to automatically detect them remains a challenge.

We deployed the emerging deep learning approaches. Precisely, we used word embedding to encode semantic information of words occurring in the common microtext of social media and used variational autoencoder (VAE) to approximate the topic modeling process, through which the active categories of influencers are automatically detected. We developed a system known as Categorical Influencer Detection (CID) to realize those ideas.

The approach of using VAE to simulate the Latent Dirichlet Allocation (LDA) process can effectively handle the task of topic modeling on the vast dataset of microtext on social media channels.

This work has two major contributions. The first one is the detection of topics on microtexts using deep learning approach. The second is the identification of categorical influencers in social media.

This work can help brands to do digital marketing on social media effectively by approaching appropriate influencers. A real case study is given to illustrate it.

In this paper, we discuss an approach to automatically identify the active categories of influencers by performing topic detection from the microtext related to the influencers in social media channels. To do so, we use deep learning to approximate the topic modeling process of the conventional approaches (such as LDA).

This paper aims to investigate the moderating effects of corporate governance mechanisms on the financial leverage–profitability relation in emerging market firms.

The paper examines the impacts by estimating the empirical model in which a firm’s accounting profitability is a dependent variable, while financial leverage, board size, board independence, CEO duality, CEO ownership, state ownership and the interaction variables are predictors. The paper uses the panel data set of 295 listed firms in Vietnam in the period 2011-2015 and two key econometric methods for panel data, namely, the two-stage least square instrumental variable and general moments method.

The paper finds the evidence for the significant and positive effect of board size, board independence and state ownership on the financial leverage–profitability relation. The effect of CEO duality on the financial leverage–profitability relation tends to be negative, and the impact CEO ownership inclines to be positive, although both of them are statistically insignificant. The results are consistent across different estimation methods.

This paper is the first investigating the moderating effect of various corporate governance mechanisms on the financial leverage–profitability relationship in emerging market firms.