The meta-argument in this article is that there has been an increasing embracement of social networks by different marketing personnel who include both market practitioners and the academia. The authors of this article claim that research has become a fundamental entity in the field of marketing, citing the Marketing Science Institute as being among the top areas of study in the recent decade. Considering that the Market is diverse and heterogeneous marketers have to understand the system so as to be able to enhance the acceptability of goods and services across cultural frameworks. However, understanding the social system cannot be achieved through the study of a single aggregate population or class. Analyzing the social system requires a continuous contact with different social groups over time. This article argues that social networks have been able to provide marketing researchers with this opportunity. In retrospect, this claim is substantial. This is because social networks today attract diverse groups and citizenries across the globe (Moody, 2004, p.31). The bringing together of different cultural diversities on a single social network allows researchers to be able to analyze the patterns and trends in consumer needs across these cultures. In addition, it is through these social networks that different preferences and tastes with regards to different products are identified.
One thing that is worth noting is that the collection of data in the social networks should not be taken at the early stages of a given social network. There is a need for researchers to make sure that the carious social networks that they use are stable. By stability, it means that the social networks have to meet a certain standard in terms of its number of members, socio-economic diversity, as well as its geographic coverage. This avoids bias that might result from the use of data that is dominated by a given class of people. This article does a great job in the capitalizing of the idea that the social networks have to be stable. This is because quantitative data in most cases can be prone to values and opinions, which can lead to data that is not value-free. The value-freeness of quantitative research methodology makes it more credible.
This article is also cautious in terms of the methodology that is used to derive data from the different trends and patterns that are identifiable within the social networks. The authors explain that there is a need to make sure that data is documented at the onset of the social network so that researchers can be able to analyze data with different timeframes. It is worth noting that time is an important factor in this type of research. This is because the interaction of different culture groups within social networks often alters the homogeneity of consumption that is evident prior to the stability of a given social network (Stremersch, 2007, p.23). Different consumers tend to propose different goods and services to their counterparts which might lead to the embracement of other tastes and preferences that are not indigenous to a given cultural group. Therefore, one of the key reasons why this article proposes that data be documented within different time frames is meant to make sure that the effects of interactions of different cultural and social groups is identifiable through the changing patterns and trends with regards to data.
The size of data collected from social networks is also a key concern that is expressed by the authors. This is an excellent observation because large data is in most cases unmanageable. This is because large data is prone to error because of the different variables involved. However using small chunks of data allows researchers to be able scrutinize the data and identify areas that might result in error. In addition, the use of small quantities of data that is proposed in this article is important for efficiency purposes. Having the same number of researchers work on small amount of data increases the accuracy because researchers are not overloaded with large quantities of work. Therefore, one of the key strength of this articles its explanation about the research methodology. The authors of this article are more concerned about the accuracy of data and not the quantity of analysis that is offered regarding different trends and patterns that are identified within a given social network. In order to enhance efficiency, the authors of this article also argue that the use of different disciplines in the analysis of data provides better results.
Mathematics is a vital discipline that can be used in deriving different formulas and standard deviations that are important both in enhancing accuracy and identifying error in data compilation (Newman, 2001, p.59). Computer science and other social science disciplines have also been cited as other disciplines that are important in the study of human behavior considering that human interaction is a key element in the social networks (Grossman and Ion, 1995, p.33). Therefore, among the key strengths in this article include the use of other disciplines in the analysis of data so as to enhance accuracy and also to clearly identify the causative agents to different behavioral patterns within social networks.
Grossman, G., & Ion, R. W. (1994). Economic transformation. Boulder, Colo.: Westview Press.
Moody, G. (2004). Digital code of life: how bioinformatics is revolutionizing science, medicine, and business. Hoboken, N.J.: Wiley.
Newman, P. (2001). Readings in mathematical economics. Baltimore: Johns Hopkins Press.
Stremersch, S. (2007). Essays on marketing strategy in technology-intensive markets. Tilburg: Center, Tilburg University.