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Hence, this article was done by using a combination of four stages of: text pre-processing, personality analysis, sentiment analysis, and a chatbot system. This article shows the effect of using the personality traits, agreeableness and emotional range, with sentiment analysis to help reaching a full description of customer feel. Combining the sentiment analysis Na\u00efve Bayes technique in the natural language processing and personality insights pre-learning stage and adding feedback using the obtained results achieves higher accuracy than using the traditional sentiment analysis techniques.<\/p>","DOI":"10.4018\/ijssmet.2020070103","type":"journal-article","created":{"date-parts":[[2020,6,9]],"date-time":"2020-06-09T09:26:43Z","timestamp":1591694803000},"page":"33-46","source":"Crossref","is-referenced-by-count":3,"title":["Tracking How a Change in a Telecom Service Affects Its Customers Using Sentiment Analysis and Personality Insight"],"prefix":"10.4018","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5201-2116","authenticated-orcid":true,"given":"Ammar","family":"Adl","sequence":"first","affiliation":[{"name":"Faculty of Computers and Information, Beni-Suef University, Egypt"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Abdelsadeq Khamis","family":"Elfergany","sequence":"additional","affiliation":[{"name":"Faculty of Computers and Information, Beni-Suef University, Egypt"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2432","reference":[{"key":"IJSSMET.2020070103-0","doi-asserted-by":"crossref","unstructured":"Aarde, N. v., Meiring, D., & Wiernik, B. 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