TY - GEN
T1 - Blog mining for the fortune 500
AU - Geller, James
AU - Parikh, Sapankumar
AU - Krishnan, Sriram
PY - 2007
Y1 - 2007
N2 - In recent years there has been a tremendous increase in the number of users maintaining online blogs on the Internet. Companies, in particular, have become aware of this medium of communication and have taken a keen interest in what is being said about them through such personal blogs. This has given rise to a new field of research directed towards mining useful information from a large amount of unformatted data present in online blogs and online forums. We discuss an implementation of such a blog mining application. The application is broadly divided into two parts, the indexing process and the search module. Blogs pertaining to different organizations are fetched from a particular blog domain on the Internet. After analyzing the textual content of these blogs they are assigned a sentiment rating. Specific data from such blogs along with their sentiment ratings are then indexed on the physical hard drive. The search module searches through these indexes at run time for the input organization name and produces a list of blogs conveying both positive and negative sentiments about the organization.
AB - In recent years there has been a tremendous increase in the number of users maintaining online blogs on the Internet. Companies, in particular, have become aware of this medium of communication and have taken a keen interest in what is being said about them through such personal blogs. This has given rise to a new field of research directed towards mining useful information from a large amount of unformatted data present in online blogs and online forums. We discuss an implementation of such a blog mining application. The application is broadly divided into two parts, the indexing process and the search module. Blogs pertaining to different organizations are fetched from a particular blog domain on the Internet. After analyzing the textual content of these blogs they are assigned a sentiment rating. Specific data from such blogs along with their sentiment ratings are then indexed on the physical hard drive. The search module searches through these indexes at run time for the input organization name and produces a list of blogs conveying both positive and negative sentiments about the organization.
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U2 - 10.1007/978-3-540-73499-4_29
DO - 10.1007/978-3-540-73499-4_29
M3 - Conference contribution
AN - SCOPUS:37249040449
SN - 9783540734987
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 379
EP - 391
BT - Machine Learning and Data Mining in Pattern Recognition - 5th International Conference, MLDM 2007, Proceedings
PB - Springer Verlag
T2 - 5th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2007
Y2 - 18 July 2007 through 20 July 2007
ER -