Arts Project Topics

New Media Advocacy and the Challenge of Authenticity: a Study of Youtube

New Media Advocacy and the Challenge of Authenticity a Study of Youtube

New Media Advocacy and the Challenge of Authenticity: a Study of Youtube

CHAPTER ONE

Objectives of the Study

To realize the aim of this study, the researcher will carry out the following activities.

  1. Do a survey of Nigerians who use the YouTube as an avenue to post, advocate and show support for advocacy campaigns
  2. Check whether those who participate; receive, share, post and contribute to content on YouTube check out information and source of materials before participation.
  3. To find out how effective the New Media has been when used as a tool for intervention and public engagement
  4. Make necessary recommendation by designing an effective way of using the YouTube for advocacy.

CHAPTER TWO

REVIEW OF RELATED LITERATURE

Introduction

There are emerging bodies of literatures and theories suggesting that the new media has great potentials for reshaping the way advocacy projects are carried out. Some are quite optimistic that the New Media will be a transformative medium (Brown, 2000, Seib, 2007) New media technologies are drivers of social change, national development and organisational development, a notion grounded in the technological determinism theory which postulates that technology has the power to drive human action and change (Lievrouw and Livingstone 2006; Ikpe and Olise 2010). Others posits that the New Media holds great potential for facilitating Civil Society, Civic engagement, and democratic participation (Moore, 2003; Ito, 2004; Jenkins, 2006b; Jenkins et al., 2006; Pettingill, 2007).

Perhaps a good starting point for this review will be Mushinge, 2008.1, who points to the fact that new media has shaped and continues to shape the way the media is produced and distributed as a result individuals can now publish in real time to a worldwide audience. She observes further that a new breed of advocates are taking the advocacy into their own hands armed with laptops, cell phones and digital cameras, these readers turned participants are transforming advocacy from an expert presentation into a conversation. The way and manner the new media is commanding attention and posing alternatives to conventional media, creating the impression that the traditional media is not doing enough to represent issues that the stand for.

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CHAPTER THREE

RESEACH METHODOLOGY

Since this work is interested in the meanings behind actions that is; in how and why of the New Media use, the researcher adopted a qualitative approach.

Population

The population under study is those who in one way or the other use the new media who may not have any formal training on media use yet are eager to contribute to the growth and freedom of expression the new media affords. The population under study cuts across several, socio- cultural, community, educational age groupings as it is mainly concerned with those who use the new media for mostly social activities and are likely to be called upon at one point or the other to participate in advocacy and humanitarian programs in Nigeria. The population under study is both adult and youth, the literate and the not too literate who every now and then share videos with others as well as participate in civil, humanitarian and advocacy projects on YouTube.

CHAPTER FOUR

PRESENTATION OF FINDINGS

NEW MEDIA PLATFORMS. Where do we acquire fake news from?

Social Media  

The omnipresent nature of social media has driven society into where everything (ranging from goods to information) is demanded at speed (Chen, Conroy and Rubin, 2015a). Through social media, third parties now have a new avenue in which they can engage in targeted advertising (as opposed to the traditional means such as billboards or news print for example) which results in a situation where, we as consumers, are often bombarded with information. As technological equipment has grown, the possibilities that come with it have expanded. We, as users have the options to share opinions, propagate data and if done correctly, the ability to organize relief and response plans during times of need. However, with this near universal access to the internet come information threats (Chen, Conroy and Rubin, 2015a).

The synergistic learning effect that online communities bring is just one aspect which our technological age is benefiting from but this too comes at a cost. The structure of feed or news displayed by online social networks is one of unanimity. Despite the fact that people may not choose who they interact with and are friends with online, selective exposure theory states that friend groups are usually consistent in thought (Bode and Vraga, 2015). To further cement this; algorithmic determination and the grouping of like-minded personnel allows for the creation of social bubbles that are formed. The outcome being an information environment with little diversity where worldviews (perhaps wrong world views too) are bolstered from one person to the next (Shao, et al., 2016; Bode and Vraga, 2015). One could say this poses a test to the sharing environment social media should accommodate for, which it does to a certain extent, but these potentially false beliefs may never leave these social bubbles (Shao, et al., 2016). Thus, this may limit the spread and exposure to fake news. This idea is one that will be discussed later in the paper. Moreover, Bode and Vraga (2015) also suggest that these filter bubbles may offer a different way for the presentation of information to argue against common misperceptions from one’s online friends.

CHAPTER FIVE

SUMMARY OF FINDINGS, CONCLUSION AND RECOMMENDATION

SUMMARY OF FINDINGS

This section has been included to support how the researcher answered the research question (and sub-questions) as well as attending to the aims and objectives that were mentioned in the background. Furthermore the researchers will state the main findings that were found during the discussion phase.

As the research question states, the main aim of this paper were to assess new media and their users can navigate the challenges of information authenticityTo do this, the researcher felt the need to answer three sub-questions. These being; off what platforms do users acquire false information from, how does false information spread on the reviewed platforms and what detection measures are in place which will lead to such content being mitigated. From the onset it became clear that the academic wanted to review and report on solutions to limit the spread of false information. The aims and objectives clearly state that society needs detection measures put in place which in turn leads to mitigation. Once such content is detected we can then work on ways to mitigate it. Mentioned throughout the discussion as well as touched upon during the introductory phases was the element of humans believing what aligns with their views. A prominent way in which false information spreads is through people only seeing what they want to. Thus, technical detection means are not all that we need. People need to expanding their thinking and begin to think critically before passing on information. The new media and search engines under review (Facebook, Twitter, Google and youtube) all have duties that go beyond providing a platform where people can share information. They have reputations to uphold and need to be seen as reliable sources of information for their users.

The discussion produced key results and findings which are now going to be stated. Spread of false information on social media platforms presents itself in many ways and forms. These included false information presented through click bait, hoaxes, rumours, and images. Online advertising seemed to be popular stream of entrance for false information and one reoccurring finding was that page views generate money and as such, advertisers are more concerned with page views and the speed at which they are generated rather than veracity of content. Another dominant finding was that of people’s online activity and how false realities are formed through interactions with like-minded people. The propagation of false information is assisted heavily by the filter bubbles formed on the reviewed social medias. Often is the case where people are viewing topics through a biased lens and conversing with people who are looking through at the same view. Corrections were deemed harder if the correction was not in line with one’s way of thinking. It was clear that prior beliefs hold a strong ground when judging new information. For many people, social networks serve as a key destination for the collection of news. It was noted on many occasions that fake news enters our realms through breaking news. Social media has the power to present news before official organisations get their hands on it and more often than not, online social medias report on breaking news before other parties. Thus, in the absence of contradictory information, people have nothing else to believe. Moreover, social media sites aggregate a user’s internet searchers and spit back wide ranges of content on their sites. This means that content is often lost from content which make the process of understanding information much harder.

Conclusion  

To review, fake news has risen to become a popular concept online. There is evidence that suggests that false information is contaminating our online environment and more specifically social networks (Chamberlain, 2009). There exists a pressing need to detect and consequently mitigate the spread of such information before the consequences become unmanageable. False information spreads all too freely on social medias such as Facebook and Twitter (Chen, Conroy and Rubin, 2015b). It was founded that people are reluctant to accept information that goes against their views and will continue believing incorrect information as long it answers questions of uncertainty for them while maintaining their perspective. Online advertising through presents itself as one form where deception can occur. The variety of ways in which false information can spread (click bait, hoaxes, rumours) enhance its capabilities of spreading (Schmierbach and Oeldorf-Hirsch, 2012). Search engines and social networks such as Google, Facebook and Twitter are crucial providers of information as breaking new hits these platforms first. Often is the case where breaking news or information relating to activity events may be fake or unverified. These platforms, however, have recognised the responsibility they have in ensuring false information to not be permitted on their sites. In addition to this there are detection measures in place to identify false information. Humans are called upon to think critically when taking information from social medias and it was further seen that people are alert to the fact they information found on these networks may be unreliable (Schmierbach and Oeldorf-Hirsch, 2012; Chen, Conroy and Rubin, 2015b). Through these social networks continuing to employ the detection mechanisms that they are, coupled with people increasing digital literacy skills, false information can be detected and thus mitigated.

RECOMMENDATIONS

As earlier suggested there existed a gap in terminology as there is no single defined term for disinformation, misinformation, and fake news. Each holding the characteristic of inaccuracy, is it possible to assign a single term that represents disinformation, misinformation, and fake news? In view of how this Systematic Literature Review was conducted the research focused on a pre-determined set of articles on fake news with no room for additional sources. Fake news is an ongoing problem and one could argue that it is in its prime. Thus, there are more cases and issues surrounding it every day. Social Networks and search engines alike are tackling this problem every day and there is room for further research to examine what they have done come the end of this dissertation. Also, fake news not only occurs through Facebook, Twitter, and Google but other engines and platforms will undoubtedly fall victim to it. Hence, fake news all over the internet can be studied. Due to space constraints and exclusion criteria mathematical, statistical, and technical detection mechanisms were not discussed in full detail but focus was rather paid to their overall concept. Further research could examine the effect of these potential systems and whether or not they should be introduced.

REFERENCES

  • Anonymous, 2012. Defining your question. PICO and PS. Hamilton. National Collaborating Centre for Methods and Tools.
  • Anonymous, 2016. Quality Assessment Tool – Review Articles. Hamilton. Health Evidence.
  • Attride-Stirling, J., 2001. Thematic networks. an analytic tool for qualitative research. Qualitative research, 1(3), pp. 385-405.
  • Bode, L. & Vraga, E. K., 2015. In Related News, That Was Wrong. The Correction of
  • Misinformation Through Related Stories Functionality in Social Media. JOURNAL OF COMMUNICATION, 65(4), pp. 619-638.
  • Boland, H., 2017. Facebook shareholders reject fake news proposal. [Online]  Available at. http.//www.telegraph.co.uk/technology/2017/06/01/facebookshareholders-reject-fake-news-proposal/ [Accessed 14 September 2017].
  • Bowden, I., 2016. How Google is tackling fake news, and why it should not do it alone. [Online]  Available at. http.//searchengineland.com/google-tackling-fake-news-not-alone-264058 [Accessed 14 September 2017].
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