  Requests are at the core of many social media systems such as question &
answer sites and online philanthropy communities. While the success of such
requests is critical to the success of the community, the factors that lead
community members to satisfy a request are largely unknown. Success of a
request depends on factors like who is asking, how they are asking, when are
they asking, and most critically what is being requested, ranging from small
favors to substantial monetary donations. We present a case study of altruistic
requests in an online community where all requests ask for the very same
contribution and do not offer anything tangible in return, allowing us to
disentangle what is requested from textual and social factors. Drawing from
social psychology literature, we extract high-level social features from text
that operationalize social relations between recipient and donor and
demonstrate that these extracted relations are predictive of success. More
specifically, we find that clearly communicating need through the narrative is
essential and that that linguistic indications of gratitude, evidentiality, and
generalized reciprocity, as well as high status of the asker further increase
the likelihood of success. Building on this understanding, we develop a model
that can predict the success of unseen requests, significantly improving over
several baselines. We link these findings to research in psychology on helping
behavior, providing a basis for further analysis of success in social media
systems.
