%0 Journal Article %1 conf/icsh/XiaZWLM18 %A Bargavi, Dirash A R | Dr. S K Manju %D 2021 %J International Journal of Trend in Scientific Research and Development %K Flask IDMB LSTM Learning Machine RNN %N 4 %P 728-732 %T LSTM Based Sentiment Analysis %U https://www.ijtsrd.comcomputer-science/data-processing/42345/lstm-based-sentiment-analysis/dirash-a-r %V 5 %X Sentimental analysis is a context based mining of text, which extracts and identify subjective information from a text or sentence provided. Here the main concept is extracting the sentiment of the text using machine learning techniques such as LSTM Long short term memory . This text classification method analyses the incoming text and determines whether the underlined emotion is positive or negative along with probability associated with that positive or negative statements. Probability depicts the strength of a positive or negative statement, if the probability is close to zero, it implies that the sentiment is strongly negative and if probability is close to1, it means that the statement is strongly positive. Here a web application is created to deploy this model using a Python based micro framework called flask. Many other methods, such as RNN and CNN, are inefficient when compared to LSTM. Dirash A R | Dr. S K Manju Bargavi "LSTM Based Sentiment Analysis" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, URL: https://www.ijtsrd.compapers/ijtsrd42345.pdf Paper URL: https://www.ijtsrd.comcomputer-science/data-processing/42345/lstm-based-sentiment-analysis/dirash-a-r

@article{conf/icsh/XiaZWLM18, abstract = {Sentimental analysis is a context based mining of text, which extracts and identify subjective information from a text or sentence provided. Here the main concept is extracting the sentiment of the text using machine learning techniques such as LSTM Long short term memory . This text classification method analyses the incoming text and determines whether the underlined emotion is positive or negative along with probability associated with that positive or negative statements. Probability depicts the strength of a positive or negative statement, if the probability is close to zero, it implies that the sentiment is strongly negative and if probability is close to1, it means that the statement is strongly positive. Here a web application is created to deploy this model using a Python based micro framework called flask. Many other methods, such as RNN and CNN, are inefficient when compared to LSTM. Dirash A R | Dr. S K Manju Bargavi "LSTM Based Sentiment Analysis" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, URL: https://www.ijtsrd.compapers/ijtsrd42345.pdf Paper URL: https://www.ijtsrd.comcomputer-science/data-processing/42345/lstm-based-sentiment-analysis/dirash-a-r }, added-at = {2021-07-15T10:07:25.000+0200}, author = {Bargavi, Dirash A R | Dr. S K Manju}, biburl = {https://www.bibsonomy.org/bibtex/210eb8390a12e967adb0ad99decf49132/ijtsrd}, ee = {https://doi.org/10.1007/978-3-030-03649-2_23}, interhash = {d4e94a9aa37e95924d0aa34595c106ed}, intrahash = {10eb8390a12e967adb0ad99decf49132}, issn = {2456-6470}, journal = {International Journal of Trend in Scientific Research and Development}, keywords = {Flask IDMB LSTM Learning Machine RNN}, language = {english}, month = jun, number = 4, pages = {728-732}, timestamp = {2021-07-15T10:07:25.000+0200}, title = {LSTM Based Sentiment Analysis }, url = {https://www.ijtsrd.comcomputer-science/data-processing/42345/lstm-based-sentiment-analysis/dirash-a-r}, volume = 5, year = 2021 }