Assignment One: The ‘It’s like the gold rush’ Article Paper Johnson, M. and Woodcock, J. (2017). ‘It’s like the gold rush: the lives and careers of professional video game streamers on Twitch. Tv. Information, Communication & Society, 22 (3), 336-351. Available from 10.1080/1369118x.2017.1386229 Coursework One: A review essay (weighted 40%) This assessment requires students to […]
When conducting research, the choice of a research design and methods influences the capacity of the researcher to develop unbiased conclusions concerning the study topic. As such, researchers develop well-planned research designs to ensure that the methods they adopt concur with their research objectives and that quality data is collected and analyzed to develop realistic answers for the pre-established research questions. The study “Playing the visibility game: How digital influencers and algorithms negotiate influence on Instagram” was conducted by Cotter (2019) to investigate how algorithms affect social realities among Instagram users. The study involved conducting a thematic analysis of online discussions on Instagram to assess how the algorithms in the social media channel shape the users’ pursuit of influence. The study found that algorithm structure may influence behaviors among users of a system or platform. This study seeks to assess compatibility between the research objectives and conclusions developed in research conducted by Cotter (2019) and establish key strengths and weaknesses associated with the methodologies utilized in the study. The study adopted a qualitative research strategy and a snowball sampling method to assess influencers’ perceptions concerning Instagram’s algorithm.
The study predominantly employed a qualitative research strategy to develop a solution for the research question. The researcher conducted a thematic analysis of online communications among influencers about Instagram’s algorithms to establish their conscious interactions with the algorithmic architecture of the social media channel. The researcher also performed keyword searches on Facebook to identify groups designed for existing and prospective influencers. Findings from keyword searches and analysis of influencers’ interactions with Instagram’s algorithmic structure were used to develop a generalized statement to answer the research question, which depicts a qualitative research strategy. According to Roulston (2019), qualitative research strategy involves a process of naturalistic inquiry that seeks to establish a detailed understanding of a social phenomenon. Studies that adopt a qualitative research strategy seek to better understand a social phenomenon through first-hand experience achieved through truthful reporting and quotations of actual conversations (Roulston 2019, p. 2259). The study conducted by Cotter gathered first-hand information concerning the influence of Instagram’s algorithmic structure on influencers’ pursuit of influence and excluded the collection and analysis of numerical data. The study also sought to establish a better understanding of the social phenomenon involving the effect of algorithms on Instagram user behaviors. The study involved a qualitative research strategy.
The use of a qualitative research strategy allowed the researcher to understand changing attitudes among members of the target group, which resulted in a more targeted research experience. The researcher analyzed shared articles on Facebook written by influencers, digital marketing specialists, and third-party companies that manage adverts on Instagram (Cotter 2019, p. 901). Analyzing such information allowed the researcher to assess the influencers’ attitudes and perceptions concerning Instagram’s algorithmic structure. The qualitative research strategy also provided a flexible approach as the researcher could shift the focus of the study from one factor to the other and change the setting across various social media channels to improve responses. Moreover, by adopting a qualitative research strategy, the researcher obtained a cost-effective research experience. Qualitative studies are less costly than quantitative research design since they do not involve studying large samples (Mahajan 2018, p. 23). For instance, the researcher analyzed information available online to develop a conclusion for the research. As such, excluding long and complicated data collection and analysis processes, such as administering interventions to a large sample, helped save on the cost and time spent during the study. Therefore, using a qualitative research strategy during the study facilitated the analysis of information collected by the researcher in a timely and cost-effective manner.
However, qualitative studies are blamed for relying upon the researcher’s experience and not collecting a statistically representative form of data. Data collected during qualitative research is influenced by the experience and perception of the researcher, which creates room for biased conclusions (Wadams and Park 2018, p. 72). For example, when analyzing the influence of Instagram’s algorithmic design on influencers’ pursuit of influence. Since the inferences developed in the study were based on the researchers’ experience with the nature of communication and content shared by influencers on Instagram, there is a possibility that the inferences developed were influenced by the researcher’s opinion regarding the influencers’ interaction with Instagram’s algorithmic structure. Also, qualitative research studies exclude a statistical representation of data. The qualitative research process provides research data from perspectives that can not be statistically measured. As a result, it becomes hard to establish the reliability of conclusions developed from qualitative studies. During the study, Cotter (2019) observed that influencers’ pursuit of influence resembled a game that was based on fixed rules encoded in Instagram’s algorithmic structure. However, the researcher does not describe the proportion of influencers who demonstrated the described behavior. Since the research involved studying human behavior, it was likely that some influencers did not demonstrate the behavior under study while the algorithm would greatly influence the activities of others. Therefore, it is hard to establish whether findings developed in the study reveal the actual situation among all Instagram users. Therefore, using a qualitative research strategy in the study makes it hard to establish the overall reliability of the conclusions developed by the researcher.
Qualitative studies also create data that is difficult to present and have no rigidity of conclusions. Due to the diversity of perspectives among individuals, the reaction to the qualitative research question can often be at two extremes. As such, it is difficult to present the distribution of data collected in a normal curve, which makes it hard to present generalized findings (Rahman 2020). It also becomes hard for audiences to approve of the truthfulness of conclusions developed through qualitative studies. For instance, although Cotter (2019) utilized realistic information collected on social media to develop a conclusion for the study, some audiences may develop different perspectives based on their experiences with Instagram’s algorithmic structure. Since the study does not present a statistical confidence interval, it would be hard to convince people with opposing perspectives concerning the relevance of the conclusions developed in the study. Also, since the researchers’ perspectives influence such studies, the data gathered is only reliable at the time it is gathered and may lose relevance as perspectives change with time. Consequently, qualitative research strategies limit data mining opportunities for researchers who may consider analyzing literature presented in the existing study during future research.
The researcher used an effective strategy to select the study participants. Since the study focused on the conscious interaction between influencers’ pursuit of influence and Instagram’s algorithmic structure, it was important to include individuals with great experience in the algorithm. As such, the researcher conducted a thematic analysis of online communications among influencers about Instagram’s algorithms. Cotter (2019) identifies that the study focused specifically on Instagram since a keen analysis of past scholarly work indicated that influencers preferred the platform. Also, the researcher chose to focus on influencers due to their high experience in social media and are capable to influence the actions of other social media users based on their knowledge, authority, and position. Therefore, the selection of cases by the researcher was justified.
However, reliance on the influencers’ perceptions regarding Instagram’s algorithmic structure might have varied with factors such as specialization, the influencers’ critical mass, and perceived usefulness. Since different influencers might have diverging objectives on social media, their specialization and objectives might significantly influence their attitudes and perceptions regarding Instagram’s algorithm. For example, influencers who seek to affect purchasing decisions of other internet users may appreciate referral tools on Instagram, while those who seek to raise awareness concerning various issues or items may appreciate sharing tools on the same social media platform. Similarly, an influencer’s attitude towards Instagram’s algorithmic structure may depend on the type of network that their social products operate on and the number of followers they have on Instagram. Additionally, different influencers may submit contrasting perceptions concerning using Instagram’s algorithmic structure based on their interests and objective for their social media presence. For instance, influencers who believe other alternative social media channels to be more useful may submit negative reactions concerning Instagram’s algorithm as opposed to those who believe in the efficiency of Instagram as a social media channel. Therefore, the selection of cases ought to have considered the influencers’ objectives when recording their remarks concerning Instagram’s algorithm.
The researcher used a snowball sampling strategy to select influencers and keep track of their online activities. The sampling strategy involved analyzing the activities of participants selected by the study subjects who the researcher had previously identified. Influencers who participated in online groups through Facebook referred other influencers, social media marketing professionals, and other third-party individuals and organizations by sharing their articles. The researcher used the referrals provided by the study participants to gain access to additional data by reviewing remarks left in the comment sections (Cotter 2019, p. 901). Such a sampling method allowed the researcher to analyze more information concerning influencers’ attitudes and Instagram’s algorithmic design that could otherwise be unavailable if the study focused mainly on the groups of influencers that were selected at the start. According to Leighton, Kardong-Edgren, Schneidereith, and Foisy-Doll (2021), a snowball sampling strategy involves primary data sources nominating other potential data sources that would equip the study with more accurate and consistent information. As a result, it becomes easier for a researcher to find subjects with useful information or experience concerning the research topic. Since Cotter (2019) sought to use anonymous Instagram and Facebook users as participants in the study, it was likely that the study could lack adequate information as some participants had little experience with Instagram’s algorithm. The researcher’s decision to use a snowball sampling strategy allowed for the retrieval of useful information from highly experienced individuals such as influencers and social media marketers. Therefore, the sampling method used in the study helped to optimize conclusions.
The sampling method is associated with several limitations, including sampling bias and margin error. Study participants refer the researcher to other individuals who might possess a greater capacity to provide the required information in research. However, such individuals are likely to refer to those they know and share similar characteristics. For instance, an influencer specializing in advocating for the sale of technological equipment may refer other individuals who engage in similar online activities. Consequently, the study experiences the risk of a sampling bias and margin error. Such irregularities could imply that the researcher focuses on a small group of people with almost similar attributes, which may impede the development of conclusive results regarding the phenomenon being studied. Moreover, since the researcher has no idea of the true distribution of the sample participating in the study, it becomes difficult to establish the overall reliability and consistency of the information collected, which might reduce the reliability of inferences developed by the researcher. Therefore, it would have been necessary for Cotter (2019) to develop a strategy to alleviate sampling bias and marginal error after implementing a snowball sampling strategy. An effective strategy could be increasing the sample size to get the study closer to the actual population and minimize sampling error. The researcher could also implement an additional data collection strategy involving the administration of online surveys to target group members. Findings from online surveys could help to establish the reliability of information collected through thematic analysis of online discussions among Instagram influencers.
The researcher did not identify any study limitations or instructions for future research. Study limitations help readers identify the study conditions and challenges that the researcher encountered to develop conclusions concerning their research questions (Theofanidis and Fountouki 2018, p. 155). Excluding the section in the study impedes a subjective learning process through which readers could assess the magnitude and impact of various irregularities or challenges encountered in research to inform strategies for future studies involving a similar or closely related topic. Failure to identify the study limitations also contradicts the ethical principle of transparency that requires researchers to outline key weaknesses in their scientific research to maintain mutual integrity and promote further progress in similar studies. The researcher also failed to provide a direction for future studies. Based on key findings from their studies, researchers ought to provide insight concerning areas that future studies should focus on and recommend strategies to overcome current limitations. It may also identify unanswered questions that future studies should focus on answering. Therefore, the researcher should have included sections for study limitations and directions for future studies in the research article.
By utilizing a qualitative research strategy and a snowball sampling method, the researcher developed useful insight concerning how digital influencers and algorithms negotiate influence on Instagram. The study predominantly employed a qualitative research strategy to develop a solution for the research question. Such a research strategy allowed the researcher to understand changing attitudes among members of the target group, which resulted in a more targeted research experience. However, qualitative studies are blamed for relying upon the researcher’s experience, not a statistical representative form of data collected and excluding a statistical representation of data. Qualitative studies also create data that is difficult to present and have no rigidity of conclusions. Since the study focused on the conscious interaction between influencers’ pursuit of influence and Instagram’s algorithmic structure, it was important to include individuals who had a great experience with the algorithm. However, reliance on the influencers’ perceptions regarding Instagram’s algorithmic structure might have varied with factors such as specialization, the influencers’ critical mass, and perceived usefulness. A snowball sampling strategy was used to select influencers and keep track of their online activities. The sampling method is associated with sampling bias and margin error. Such issues could have been avoided by by increasing the sample size and introducing an additional data collection strategy to get the study closer to the actual population and minimize sampling error. The researcher did not identify any study limitations and instructions for future research, which contradicts the ethical principle of transparency in research.
Cotter, K., 2019. Playing the visibility game: How digital influencers and algorithms negotiate influence on Instagram. New Media & Society, 21(4), pp.895-913.
Roulston, K., 2019. Preparing researchers to conduct interdisciplinary, multi-method qualitative research. The Qualitative Report, 24(9), pp.2259-2292. https://search.proquest.com/openview/7dc81d1d93c516dc7909a0233f6516e8/1?pq-origsite=gscholar&cbl=55152
Mahajan, H.K., 2018. Qualitative research methodology in social sciences and related subjects. Journal of Economic Development, Environment, and People, 7(1), pp.23-48. https://www.ceeol.com/search/article-detail?id=640546
Wadams, M. and Park, T., 2018. Qualitative research in correctional settings: Researcher bias, western ideological influences, and social justice. Journal of forensic nursing, 14(2), pp.72-79. https://journals.lww.com/forensicnursing/Fulltext/2018/06000/Qualitative_Research_in_Correctional_Settings_.4.aspx
Rahman, M.S., 2020. The advantages and disadvantages of using qualitative and quantitative approaches and methods in language “testing and assessment” research: A literature review. https://pearl.plymouth.ac.uk/handle/10026.1/16598
Leighton, K., Kardong-Edgren, S., Schneidereith, T. and Foisy-Doll, C., 2021. Using social media and snowball sampling as an alternative recruitment strategy for research. Clinical Simulation in Nursing, 55, pp.37-42. https://www.sciencedirect.com/science/article/pii/S1876139921000360
Theofanidis, D. and Fountouki, A., 2018. Limitations and delimitations in the research process. Perioperative Nursing-Quarterly scientific, online official journal of GORNA, 7, pp.155-163. https://www.spnj.gr/en/limitations-and-delimitations-in-the-research-process-p160.html
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Published On: 01-01-1970