23. An apparatus, comprising: a memory configured to store social signal data based on social signals published using social media accounts, the social signal data including first information that includes a content of the social signals and second information that is different than the first information, wherein the second information includes metadata; and a processor configured to: identify conversations in the social signals using said second information; group the conversations into topic clusters using the first information, including; form a first set of topic clusters that corresponds to a first time; and form one or more second sets of topic clusters that correspond to one or more second different times, respectively; and wherein, responsive to the grouping using the first information, a first one of the conversations is grouped with a second one of the conversations into a same one of the topic clusters of the first set or the one or more second sets, the first one of the conversations based on a root social signal of the social signals that is not explicitly linked, by the second information, with a different root social signal on which the second one of the conversations is based; and link the topic clusters together into a plurality of conversation streams, wherein a first conversation stream of the plurality of conversation streams includes a topic cluster of the first set and at least one associated topic cluster of the one or more second sets, and wherein a second conversation stream of the plurality of conversation streams includes a different topic cluster of the first set and at least one associated topic cluster of the one or more second sets; calculate strengths of the different conversation streams based on a quantity of the social signals contributing to the conversation streams and a quantity and types of followers associated with the conversation streams; and derive a score for one of the social media accounts based on the strengths of the conversation streams.
23. An apparatus, comprising: a memory configured to store social signal data based on social signals published using social media accounts, the social signal data including first information that includes a content of the social signals and second information that is different than the first information, wherein the second information includes metadata; and a processor configured to: identify conversations in the social signals using said second information; group the conversations into topic clusters using the first information, including; form a first set of topic clusters that corresponds to a first time; and form one or more second sets of topic clusters that correspond to one or more second different times, respectively; and wherein, responsive to the grouping using the first information, a first one of the conversations is grouped with a second one of the conversations into a same one of the topic clusters of the first set or the one or more second sets, the first one of the conversations based on a root social signal of the social signals that is not explicitly linked, by the second information, with a different root social signal on which the second one of the conversations is based; and link the topic clusters together into a plurality of conversation streams, wherein a first conversation stream of the plurality of conversation streams includes a topic cluster of the first set and at least one associated topic cluster of the one or more second sets, and wherein a second conversation stream of the plurality of conversation streams includes a different topic cluster of the first set and at least one associated topic cluster of the one or more second sets; calculate strengths of the different conversation streams based on a quantity of the social signals contributing to the conversation streams and a quantity and types of followers associated with the conversation streams; and derive a score for one of the social media accounts based on the strengths of the conversation streams. 33. The apparatus of claim 23 , wherein group the conversations into topic clusters using the first information further comprises: generating a first term vector for the first conversation, the first term vector for the first conversation including terms of the social signals of the first conversation; generating a second term vector for the second conversation, the second term vector for the second conversation including terms of the socials of the second conversation; and grouping the first and second conversations into a same one of the topic clusters of the first set or the one or more second sets based on similarity of the first and second term vectors.