Monitoring the Quality and Perception of Service in Colombian Public Service Companies with Twitter and Descriptive Temporal Analysis
The main goal of this research is to analyze the perception of service in public sector companies in the city of Bogota via Twitter and text mining to identify areas, problems, and topics aiming for quality service improvement. To achieve this objective, a structured method for data modeling is impl...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-09-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/13/18/10338 |
| _version_ | 1797581384690171904 |
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| author | Dante Conti Carlos Eduardo Gomez Juan Guillermo Jaramillo Victoria Eugenia Ospina |
| author_facet | Dante Conti Carlos Eduardo Gomez Juan Guillermo Jaramillo Victoria Eugenia Ospina |
| author_sort | Dante Conti |
| collection | DOAJ |
| description | The main goal of this research is to analyze the perception of service in public sector companies in the city of Bogota via Twitter and text mining to identify areas, problems, and topics aiming for quality service improvement. To achieve this objective, a structured method for data modeling is implemented based on the KDD methodology. Tweets from January to June 2022 related to the companies in the sector are processed, and a temporal analysis of the evolution of sentiment is performed based on the dictionaries Bing, AFINN, and NRC. Subsequently, the LDA algorithm (Latent Dirichlet Allocation algorithm) is used to visually identify the topics with the greatest negative impact reported by the users in each of the 6 months by adding the temporal dimension. The results revealed that, for Aqueduct (water supply service), the topic with the highest dissatisfaction is related to the “Water Tank Request” processes; for Enel (energy services) “Service Outages”; and for Vanti (gas services), “Case solution and request information”. Temporal patterns of tweets, sentiments, and topics are also highlighted for the three companies. |
| first_indexed | 2024-03-10T23:04:29Z |
| format | Article |
| id | doaj.art-92778ef4595748a7bbc0007c978a3428 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T23:04:29Z |
| publishDate | 2023-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-92778ef4595748a7bbc0007c978a34282023-11-19T09:26:21ZengMDPI AGApplied Sciences2076-34172023-09-0113181033810.3390/app131810338Monitoring the Quality and Perception of Service in Colombian Public Service Companies with Twitter and Descriptive Temporal AnalysisDante Conti0Carlos Eduardo Gomez1Juan Guillermo Jaramillo2Victoria Eugenia Ospina3Departament of Statistics & Operations Research, Universidad Politécnica de Cataluña, 08034 Barcelona, SpainMaestría en Gestión de Información, Escuela Colombiana de Ingeniería Julio Garavito, Bogotá 111116, ColombiaMaestría en Gestión de Información, Escuela Colombiana de Ingeniería Julio Garavito, Bogotá 111116, ColombiaMaestría en Gestión de Información, Escuela Colombiana de Ingeniería Julio Garavito, Bogotá 111116, ColombiaThe main goal of this research is to analyze the perception of service in public sector companies in the city of Bogota via Twitter and text mining to identify areas, problems, and topics aiming for quality service improvement. To achieve this objective, a structured method for data modeling is implemented based on the KDD methodology. Tweets from January to June 2022 related to the companies in the sector are processed, and a temporal analysis of the evolution of sentiment is performed based on the dictionaries Bing, AFINN, and NRC. Subsequently, the LDA algorithm (Latent Dirichlet Allocation algorithm) is used to visually identify the topics with the greatest negative impact reported by the users in each of the 6 months by adding the temporal dimension. The results revealed that, for Aqueduct (water supply service), the topic with the highest dissatisfaction is related to the “Water Tank Request” processes; for Enel (energy services) “Service Outages”; and for Vanti (gas services), “Case solution and request information”. Temporal patterns of tweets, sentiments, and topics are also highlighted for the three companies.https://www.mdpi.com/2076-3417/13/18/10338LDAtopic modelingTwittertemporal analysissentiment analysis |
| spellingShingle | Dante Conti Carlos Eduardo Gomez Juan Guillermo Jaramillo Victoria Eugenia Ospina Monitoring the Quality and Perception of Service in Colombian Public Service Companies with Twitter and Descriptive Temporal Analysis Applied Sciences LDA topic modeling temporal analysis sentiment analysis |
| title | Monitoring the Quality and Perception of Service in Colombian Public Service Companies with Twitter and Descriptive Temporal Analysis |
| title_full | Monitoring the Quality and Perception of Service in Colombian Public Service Companies with Twitter and Descriptive Temporal Analysis |
| title_fullStr | Monitoring the Quality and Perception of Service in Colombian Public Service Companies with Twitter and Descriptive Temporal Analysis |
| title_full_unstemmed | Monitoring the Quality and Perception of Service in Colombian Public Service Companies with Twitter and Descriptive Temporal Analysis |
| title_short | Monitoring the Quality and Perception of Service in Colombian Public Service Companies with Twitter and Descriptive Temporal Analysis |
| title_sort | monitoring the quality and perception of service in colombian public service companies with twitter and descriptive temporal analysis |
| topic | LDA topic modeling temporal analysis sentiment analysis |
| url | https://www.mdpi.com/2076-3417/13/18/10338 |
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