Title: Development of Document Transferring and Archiving Service with Sentiment Analysis-based Preprocessing Facility

Year of Publication: Jul - 2017
Page Numbers: 160-165
Authors: Shunsuke Doi, Yoshiro Imai, Kazuaki Ando, Koji Kagawa, Rihito Yaegashi, Keizo Saisho, Kyosuke Takahashi, Hitoshi Inomo, Naka Gotoda, Toshihiro Hayashi, Hiroyuki Tominaga, Tomohiko Takagi
Conference Name: The Third International Conference on Electronics and Software Science (ICESS2017)
- Japan


People used to be writing several kinds of docu- ments such as memoranda, message, e-mail etc. for the third persons to read possibly with emo- tional feeling. After they prepared the above doc- uments, sometimes such documents might unin- tentionally hurt other’s heart due to our careless emotional expressions. If some kind of checking services were utilized for the above careless emo- tional expressions, people could avoid to write doc- uments which would unintentionally hurt other’s heart. This paper describes our newly developed Document Transferring and Archiving Service with Sentiment Analysis-based Preprocessing Facility. It is realized as server-client computing model, namely its server is written in Perl and PHP just like LAMP(Linux-Apache-MySQL-PHP/Perl) and its client is written in JavaScript executing on the major Browsers. The service can scan the regard- ing document of a user, separate it into word-level expressions, check them against sentiment dictio- nary, calculate each sentimental values for docu- ment and generate the corresponding radar chart for the document based on emotional axises such as delight, anger, sorrow, pleasure and so on. Users, namely writers, use our Service before transferring and/or archiving, they can check their documents by means of the above preprocessing facility and recognize how their ones have a lot of emotional feelings which would include non-suitably emo- tional expressions. With such a service, users of the service can avoid to write, transfer or archive such documents which would unfortunately make someone feel bad.