Leveraging Social Media to Assist in Troubleshooting

An article of manufacture comprising a non-transitory computer readable storage medium having computer readable instructions tangibly embodied thereon which, when implemented, cause a computer to carry out a plurality of method steps comprising:

• extracting user-generated information pertaining to multiple failure scenarios from at least one social media data source;
• determining one or more causality relationships between a set of log entries associated with the multiple failure scenarios and the extracted user-generated information;
• identifying a similarity between the one or more determined causality relationships and information contained within a user query;
• and
• providing guidance to the user regarding resolving and/or obviating one or more failures associated with the user query based on said identified similarity, wherein said guidance comprises multiple alerts associated with multiple failures, and wherein said providing comprises:
• prioritizing said multiple alerts based on (i) a computed severity of each of the multiple failures, (ii) an expected lead time to failure associated with each of the multiple failures, and (iii) a computed confidence value associated with each of the one or more determined causality relationships.

A system comprising:

• a memory;
• and
• at least one processor coupled to the memory and configured for:
• extracting user-generated information pertaining to multiple failure scenarios from at least one social media data source;
• determining one or more causality relationships between a set of log entries associated with the multiple failure scenarios and the extracted user-generated information;
• identifying a similarity between the one or more determined causality relationships and information contained within a user query;
• and
• providing guidance to the user regarding resolving and/or obviating one or more failures associated with the user query based on said identified similarity, wherein said guidance comprises multiple alerts associated with multiple failures, and wherein said providing comprises:
• prioritizing said multiple alerts based on (i) a computed severity of each of the multiple failures, (ii) an expected lead time to failure associated with each of the multiple failures, and (iii) a computed confidence value associated with each of the one or more determined causality relationships.

A method comprising:

• extracting user-generated information pertaining to multiple failure scenarios from at least one social media data source;
• determining one or more causality relationships between a set of log entries associated with the multiple failure scenarios and the extracted user-generated information;
• computing a confidence value associated with each of the one or more determined causality relationships;
• identifying a similarity between the one or more determined causality relationships and information contained within a user query;
• and
• providing guidance to the user regarding resolving and/or obviating one or more failures associated with the user query based on said identified similarity and said computed confidence value associated with each of the one or more determined causality relationships, wherein said guidance comprises multiple alerts associated with multiple failures, and wherein said providing comprises:
• prioritizing said multiple alerts based on (i) a computed severity of each of the multiple failures, (ii) an expected lead time to failure associated with each of the multiple failures, and (iii) said computed confidence value associated with each of the one or more determined causality relationships;
• wherein at least one of said extracting, said determining, said computing, said identifying, and said providing is carried out by a computing device.