## 5 Conclusions  
This research contributes to two lines of theoretical study. It augments the literature on 2 SMs through the identification of factors that explain the effect of different types of messages in social networks. It adds to the research into online content and information use in general, supported by the ELM, by providing explanations on how media metrics influence the effect of two types of messages. The literature review showed that in online environments, compliance with social norms can emerge in different ways compared to face-to-face interaction [20]. Moreover, it is still unclear which elements can have the power to influence individuals' behavior during online communication processes [2], calling for more specific explanations. It was speculated that the effect of 1 SMs and 2 SMs in social networks could be different in comparison to their effects in traditional media, because of particularities in media metrics and its effects on a customer's responses [30]. In addition, direct information seeking and involuntary exposure to information increasingly take place on social media platforms, such as Facebook, YouTube, and Instagram [45], increasing the customer's exposure to 2 SMs. In this scenario, the first theoretical contribution of this investigation is the proposition and testing of the interaction effect between the type of message (1 SM and 2 SM) and the media metrics of the vlog on customers' responses. The results confirmed that the effect of 1 SMs on attitude towards the vlog is more positive with a high YouTube's media metrics than without that information and that the effect of 2 SMs on attitude towards the vlog is more positive without information about a YouTube's media metrics than with a high YouTube's media metrics information. Regarding 1 SMs, this confirmation supports previous studies on online content and information literature [27; 30; 39] that based their explanations on the bandwagon heuristic [33]. Regarding 2 SMs, it also supports previous research in two-sided perception [2; 8; 9; 15] and in computer-mediated communication [44]. Based on our results and theoretical explanations, media metrics of social networks must be considered as a moderator factor of the effect of different types of message. However, this confirmation needs replication efforts in future research. It is possible that subjects in the 2 SM condition may have believed that they were being tested for their ability to perceive the negative side of the product and their responses, lowering attitudes, were somehow an attempt to demonstrate this ability. Additionally, the proposition and testing of the interaction effect between type of message and a YouTube's media metrics on customers' responses was supported only for the dependent variable attitude towards the vlog. Attitudes towards the product and the brand inserted in the message were not influenced by the proposed independent variables. This is evidence that the type of message and media metrics of the vlog do not have enough power to influence evaluations of the announced product. This result confirms previous research, which demonstrated that Internet users rely mostly on surface characteristics and features rather than on content evaluation to give likes and shares [30]. This research extends the examination of the effect of media metrics on attitudes towards the vlog. A possible explanation for the lack of confirmation of H2 and H3 could be that information about the media metrics of the vlog is insufficient to increase an individual's confidence enough to make a judgment of the product and the brand. In previous research, conformity intention to social norms was analyzed as a dependent variable of individuation and deindividuation processes [45]. We proposed a new perspective for the analysis of conformity intention focusing on conformity intention to others' opinion in social networks.