Matthewjockers.net Website Review

On Friday I posted an updated version of Syuzhet (1.0.4) to CRAN. This version has been available over on GitHub by using the expanded NRC lexicon from Saif Mohammed. The lexicon includes sentiment values for 13,901 words in each of the following French, German, Greek, Gujarati, Hebrew, Hindi, Irish, Italian, Japanese, Latin, Marathi, Persian, Portuguese, Romanian, Russian, Somali, Spanish, Sudanese, Swahili, Swedish, Tamil, Telugu, Thai, Turkish, Ukranian, Urdu, Vietnamese, Welsh, Yiddish, Zulu. At the time of this release, however, Syuzhet will only work with languages that use Latin character sets. This effectively means that “Hindi”, “Japanese”, “Marathi”, “Persian”, “Russian”, “Tamil”, “Telugu”, “Thai”, “Ukranian”, “Urdu”, “Yiddish” are not supported even though these languages are part of the extended NRC dictionary and can be accessed that the German, French, and Spanish results seem to be good. Your mileage may vary. For details on the lexicon, see NRC Emotion Lexicon Also in this release is support for user created lexicons. To work, users create their own custom lexicon as a data frame with at least two columns named “word” and “value.” Here is a simplified example: cluster information from parallel::makeCluster() to achieve results quicker on systems with multiple cores. Examples of how to use these new functions and languages are in the updated vignette.. ≈ COMMENTS OFF ON RESURRECTING A LOW PAS* FILTER (WELL, KIND OF) that the smoothing filter as I had implemented it in the beta version of Syuzhet was not performing satisfactorily. Ben Schmidt had that the method was producing an unacceptable “ringing” artifact. Within days of posting the “requiem,” I began hearing from people in the signal processing community offering solutions and suggesting I might have given up on the low pas* filter too soon. transfomred signal. McGuire’s changes addressed some of the issues and were rolled into the next version of the package.