scholarly journals The Management of Digital Marketing Strategies in Social Network Services: A Comparison between American and European Organizations

Author(s):  
Luis Matosas-López

The present study aims to provide an overview of the digital marketing strategies in social network services (SNSs) used in America and Europe. This work, unlike previous research that analyze digital marketing strategies in SNSs in a single geographic area, presents as the main contribution and value the use of a comparative approach between continents; specifically, then, an approach that allows comparing the management strategies used in these two areas. The research takes a sample of forty organizations, twenty American and twenty European. The author applies a descriptive examination followed by a parametric analysis using the t-test procedure over a total of 158,208 publications on Twitter. The findings show significant differences in the management approaches applied in these two continents. Even though the digital marketing strategies in SNSs should be based on dialogue and interaction with the organization’s target audience, this point can be more or less important, depending on the continent. While European organizations confer great importance to the interaction with its audience, American organizations tolerate a greater degree of one-way communication. The author concludes that the paradigms governing the definition of digital marketing strategies in SNSs at the global level, a priori thought to be universal, probably require reformulation if they are to be well adapted to the specific geographic areas where these strategies are implemented.

2021 ◽  
Vol 11 (6) ◽  
pp. 2530
Author(s):  
Minsoo Lee ◽  
Soyeon Oh

Over the past few years, the number of users of social network services has been exponentially increasing and it is now a natural source of data that can be used by recommendation systems to provide important services to humans by analyzing applicable data and providing personalized information to users. In this paper, we propose an information recommendation technique that enables smart recommendations based on two specific types of analysis on user behaviors, such as the user influence and user activity. The components to measure the user influence and user activity are identified. The accuracy of the information recommendation is verified using Yelp data and shows significantly promising results that could create smarter information recommendation systems.


2014 ◽  
Vol 71 (6) ◽  
pp. 2035-2049 ◽  
Author(s):  
Feng Jiang ◽  
Seungmin Rho ◽  
Bo-Wei Chen ◽  
Xiaodan Du ◽  
Debin Zhao

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