%0 Journal Article %1 fenggovernment %A Feng, Xuan %D 2022 %J BOHR International Journal of Data Mining and Big Data %K CommercialMedia DataMinin MachineLearning Methodology NLP NatureLanguageProcessing TextMining XML %N 1 %P 26-31 %R https://doi.org/10.54646/bijdmbd.004 %T Do US Government and Commercial Media Concern Similar Topics? – A Text-mining (NLP) Approach %U https://www.bohrpub.com/article/BIJDMBD/Vol1N1/BIJDMBD_20221104.pdf %V 1 %X Text Mining and nature language processing (NLP) has become an important tool in many research areas. Text Mining is the discovery by computer of new, previously unknown information, by automatically extracting information from different written resources. This task conducted a series of text mining jobs mainly based on the New York Times news titles corpus from Jan 2020 to Apr 2021. This task also did some analyses based on the US congressional speeches during the same period. The result shows that compared with the focuses of US congressional speeches, the focuses of New York Times news titles better reflected the changing hotspot issues over time

@article{fenggovernment, abstract = {Text Mining and nature language processing (NLP) has become an important tool in many research areas. Text Mining is the discovery by computer of new, previously unknown information, by automatically extracting information from different written resources. This task conducted a series of text mining jobs mainly based on the New York Times news titles corpus from Jan 2020 to Apr 2021. This task also did some analyses based on the US congressional speeches during the same period. The result shows that compared with the focuses of US congressional speeches, the focuses of New York Times news titles better reflected the changing hotspot issues over time}, added-at = {2022-05-25T11:36:59.000+0200}, author = {Feng, Xuan}, biburl = {https://www.bibsonomy.org/bibtex/202798734a287a4aad1ed7eb8b7814416/ijdmbdjournal}, doi = {https://doi.org/10.54646/bijdmbd.004}, interhash = {e42d9000eecbea6c5d9c577dabe52e29}, intrahash = {02798734a287a4aad1ed7eb8b7814416}, journal = {BOHR International Journal of Data Mining and Big Data}, keywords = {CommercialMedia DataMinin MachineLearning Methodology NLP NatureLanguageProcessing TextMining XML}, language = {English}, month = may, number = 1, pages = {26-31}, timestamp = {2022-05-25T11:36:59.000+0200}, title = {Do US Government and Commercial Media Concern Similar Topics? – A Text-mining (NLP) Approach}, url = {https://www.bohrpub.com/article/BIJDMBD/Vol1N1/BIJDMBD_20221104.pdf}, volume = 1, year = 2022 }