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Karen Z
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Update readme and complete gridsearch
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.ipynb_checkpoints/gfg_3_pipeline_eval-checkpoint.ipynb

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README.md

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# go-for-gold
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User-generated content has the potential to achieve virality quickly.
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Sometimes referred to as 'campaign' even. Some hashtags die, others become part of world history.
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Typically user-generated viral content is... what? Pithy? Heartstring tugger?
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"Early responses" carry cultural weight that buys cultural capital, as evidenced by the "FIRST" or "INB4" internet trends. Cultural capital can translate to real capital for a retail or political enterprise, or more directly to an organization that seeks increased "views" on its ads.
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"Early response" can also create the impression of authenticity with the public, with later responses being more and more likely to invoke the suspicion of "bandwagonism".
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There is a psychological phenomenon of "social proof" (??? better one???), which in this case: an early, independent "endorsement" of a statement that has innate potential to catch a lot of eyes can stimulate the process of virality, or even possibly serve as the catalyst in that process.
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The ability to foresee the imminent virality of user-generated content in the social media space is therefore valuable.
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This model assumes that response/recognition is cheap, but missed opportunities are expensive. Therefore it aims to catch as many "peer-endorsement-potentials" as possible (true positives), even if it means mistakenly flagging others (false positives).
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Go For Gold
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========
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Predicting early endorsement in user-generated content
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========
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Context
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---------
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User-generated content has the potential to achieve virality quickly, to the point where such content is even referred to as a 'campaign' - after it has already become one, that is. Some hashtags die, others become part of world history.
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Consumers have become more savvy to the fabricated nature of many traditional forms of social proof, such as 'ambassador-style' brand advocates or "most popular" product sales. In the social media space in particular, one form of social proof retains an air of authenticity: the "early" response and/or endorsement. "Early" responses to content that has latent viral potential carry cultural weight that buys cultural capital, whereas later responses become more likely to invoke the suspicion of "bandwagonism".
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Early endorsement of potentially viral user-generated content represents a brand "spending" attention on something that does not have an immediate obvious payback in terms of exposure (thus gaining perceived authenticity).
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Objective
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The ability to foresee the imminent virality of user-generated content in the social media space is therefore valuable. Additionally, latent viral potential and presence of early endorsements tend to correlate, with a synergistic effect.
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Therefore, this text classifier:
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* seeks to identify user-generated content likely to attract early endorsement, in order to "beat" the crowd and get "inb4" the bandwagon effect
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* specifically, classifies those top-level comments from a sub-forum that focuses on user-generated content, and that has a mechanism for giving public endorsement to comments (Reddit gold)
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* assumes that responding is relatively cheap, while missed opportunities are more expensive. Therefore it aims to catch as many "endorsement-potentials" as possible (true positives), even if it means mistakenly flagging others (false positives).
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