  YouTube has become the second most popular website according to Alexa, and it
represents an enticing platform for scammers to attract victims. Because of the
computational difficulty of classifying multimedia, identifying scams on
YouTube is more difficult than text-based media. As a consequence, the research
community to-date has provided little insight into the prevalence, lifetime,
and operational patterns of scammers on YouTube. In this short paper, we
present a preliminary exploration of scam videos on YouTube. We begin by
identifying 74 search queries likely to lead to scam videos based on the
authors' experience seeing scams during routine browsing. We then manually
review and characterize the results to identify 668 scams in 3,700 videos. In a
detailed analysis of our classifications and metadata, we find that these scam
videos have a median lifetime of nearly nine months, and many rely on external
websites for monetization. We also explore the potential of detecting scams
from metadata alone, finding that metadata does not have enough predictive
power to distinguish scams from legitimate videos. Our work demonstrates that
scams are a real problem for YouTube users, motivating future work on this
topic.
