Methods and a system are provided. A method includes optimizing, by a natural language processing based response optimizer having a processor, responses in an online question and answer session using natural language processing. The optimizing step includes deriving a candidate answer to a question posed in natural language and gathering support for the candidate answer by accessing a social network. The support is weighted by at least one of degree centrality, betweenness centrality, closeness centrality, Eigenvalue, hub, and authority of nodes in the social network that are associated with the support.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method, comprising: optimizing, by a natural language processing based response optimizer having a processor, responses in an online question and answer session using natural language processing, wherein said optimizing step includes: deriving a candidate answer to a question posed in natural language; gathering support for the candidate answer by accessing a social network, wherein the support is weighted by at least one of degree centrality, betweenness centrality, closeness centrality, Eigenvalue, hub, and authority of nodes that are associated with the support, from among a plurality of nodes in the social network. 2. The method of claim 1, wherein gathering support comprises performing an analysis of at least one of content, users, relationships, and sending and receiving of messages in the social network. 3. The method of claim 2, wherein performing the analysis comprises analyzing message content in the social network, and at least one of message content of instant messages, message timing, social network connectivity, instant message connectivity, and characteristics of users, tools and systems relating to the social network. 4. The method of claim 2, further comprising assigning a weight to the candidate answer responsive to a degree centrality of a node associated with the candidate answer, the degree centrality determined by the analysis, the weight being indicative of a confidence in the candidate answer. 5. The method of claim 1, further comprising computing a price, start time, and deadline associated with soliciting information from the social network. 6. The method of claim 1, further comprising estimating a utility of the candidate answer with respect to the social network and a network quality. 7. The method of claim 6, wherein the utility of the candidate answer is estimated based on a quality of past responses and an impact of the utility on the confidence level. 8. The method of claim 1, wherein the social network comprises at least one of social media accounts, instant messaging accounts, email accounts, system and event logs, and on-line bulletin board discussions. 9. The method of claim 1, wherein the social network comprises at least one social network to which a user that posed the question belongs, and performing the analysis comprises providing a suggestion of how the user can find information for the candidate answer from among members of the at least one social network to which the user that posed the question belongs. 10. The method of claim 1, wherein the candidate answer is derived from one of information directly extracted from a social network, weighting information from multiple sources based on respective degree centralities of the multiple sources derived from an analysis of the social network, and information extracted from the social network that permits additional active learning queries to individuals indirectly connected to an active learning system through the social network. 11. The method of claim 1, further comprising directing active learning to particular nodes from among the plurality of nodes in a social network based on at least one of the degree centrality, the betweenness centrality, the closeness centrality, the Eigenvalue, the hub, and the authority of the nodes in the social network that are associated with the support, wherein directing active learning comprises instructing at least one of the particular nodes on how to seek information from at least one other of the plurality of nodes. 12. The method of claim 1, wherein gathering support comprises performing a social network analysis that involves scanning message content in the social network based on discussion context and user-expertise-level, and discovering related information for increasing a confidence level of the candidate answer. 13. A method, comprising: performing active learning using a machine learning question answering system, wherein said performing step includes: directing active learning to particular nodes from among a plurality of nodes in a social network based on at least one of degree centrality, betweenness centrality, closeness centrality, Eigenvalue, hub, and authority of nodes that are associated with the support, from among a plurality of nodes in the social network. 14. The method of claim 13, wherein directing active learning comprises instructing at least one of the particular nodes on how to seek information from at least one other of the plurality of nodes.