Introduction
The Seventh Round Rumble: Facebook Live, NFL Draft Coverage, and the Algorithm's Bias The 2017 NFL Draft, broadcast across multiple platforms, offered a fascinating case study in the evolving media landscape. Specifically, Facebook Live’s coverage of the seventh round – traditionally a low-key affair – presented a unique experiment in real-time fan engagement, raising questions about the platform's role in shaping public perception and the inherent biases within algorithmic curation. This investigation delves into the complexities of that Facebook Live stream, focusing on the live grades and reactions surrounding the final round picks. Thesis: The Facebook Live coverage of the 2017 NFL Draft's seventh round, while seemingly offering democratized access to fan reaction, inadvertently amplified pre-existing biases through algorithmic filtering and selection, potentially distorting the public's understanding of late-round draft prospects and their eventual impact on the league. The seventh round of the NFL Draft is notorious for its unpredictable nature. Teams often gamble on raw talent or project players with question marks. Therefore, any live commentary, especially fan-driven reactions, lacks the analytical depth of established sports journalism. Yet, Facebook Live presented this raw, unfiltered response directly to a potentially massive audience. The platform's algorithm, however, played a crucial role in shaping what this audience saw. Unlike traditional television broadcasts with curated panels of experts, Facebook Live relies heavily on its algorithm to promote engaging content, often prioritizing virality over accuracy or nuanced perspectives. Evidence suggests the algorithm disproportionately favored highly emotional, often negative, reactions. Comments expressing outrage over a team's pick or highlighting perceived flaws in a player gained far more visibility than measured analyses or positive appraisals. This is consistent with research on social media algorithms, which indicates a tendency towards "engagement-maximizing" content, regardless of its informational value (Pariser, 2011).
Main Content
For example, a short video of a fan reacting hysterically to a seemingly "bad" pick likely received more algorithmic boost than a longer, reasoned discussion of the player’s potential. This resulted in a skewed representation of public sentiment. The platform effectively created an echo chamber, emphasizing negativity and potentially reinforcing pre-existing biases against specific players or teams. Different perspectives on this phenomenon exist. Proponents of Facebook Live’s approach argue that it provided an unprecedented level of fan participation and democratized access to the draft. They contend that the raw, unfiltered reactions are inherently valuable and reflect authentic fan engagement. This perspective aligns with the argument that social media platforms can foster a more participatory and inclusive media environment (Jenkins, 2006). However, critics argue that the platform’s algorithm-driven nature skewed this "democratization," creating a biased representation of public opinion. They highlight the potential for algorithmic bias to amplify negative sentiments and marginalize more thoughtful analyses. This raises concerns about the accuracy of information dissemination and the platform's responsibility in curating its content (Gillespie, 2010). The lack of context and editorial oversight means that viewers were exposed to a potentially distorted view of the event, potentially affecting their own judgments about the draft and its participants. The impact of this skewed coverage extended beyond immediate reactions. The amplified negativity surrounding certain picks could have long-term consequences for the players involved.
The public perception fostered by the Facebook Live stream, even if largely based on emotionally charged responses, could have influenced media narratives and potentially affected the players' opportunities. This exemplifies the broader issue of how social media algorithms can shape reputations and influence career trajectories, irrespective of the objective merit. In conclusion, the Facebook Live coverage of the 2017 NFL Draft's seventh round offers a compelling case study in the complexities of algorithmic curation and its impact on public perception. While seemingly offering a platform for democratized fan engagement, the platform's inherent biases, particularly its engagement-maximizing algorithm, skewed the representation of public opinion, prioritizing emotional reactions over reasoned analysis. This raises crucial questions about the responsibility of social media platforms in disseminating information and the potential for algorithmic bias to distort the public’s understanding of significant events. Future research should explore further the interplay between algorithmic curation, user behavior, and the resulting narratives on platforms like Facebook Live, paying particular attention to the potential for lasting consequences on those impacted. References: * Gillespie, T. (2010). The relevance of algorithms. In *Media technologies: Essays on communication, materiality, and society* (pp. 167-194). MIT press. * Jenkins, H.
(2006). *Convergence culture: Where old and new media collide*. NYU Press. * Pariser, E. (2011). *The filter bubble: What the Internet is hiding from you*. Penguin Press. (Note: The character count is approximate and may vary slightly depending on formatting. Finding specific data on the 2017 NFL Draft Facebook Live analytics is challenging due to the proprietary nature of Facebook's data. The references provided are general examples relevant to the discussion. More specific references could be added with access to relevant data and research. ).
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