A Public complaints data mining and visualization tool for social media: a case of Nairobi City County

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dc.contributor.authorOlweru, Stephanie
dc.date.accessioned2021-07-28T13:04:34Z
dc.date.available2021-07-28T13:04:34Z
dc.date.issued2020-04
dc.descriptionThesis Submitted to the Faculty of Information in partial fulfillment of the requirements for the award of Master of Science in Information Technologyen_US
dc.description.abstractThe government of Kenya has been experiencing low levels of public complaint feedback with regards to the current complaint reporting methods. Citizens consider the organized public meetings and office visits as time consuming and opt out of the complaint reporting process. However, citizens have been taken to complaining on social media to express their dissatisfaction with infrastructural service delivery by government. Recent efforts to improve low levels of interaction between governments and their citizens by mining data from social media have proven that citizen sourcing from social media is a suitable approach to solving this issue. Social media posts, comments, likes, favourites, shares, retweets and similar features are clear indicators of public feedback if the posts are related to public service. This study proposed the development of a tool that extracts and visualizes public complaints relating to Nairobi county from social media. Roads were the focus infrastructure category for the study. For classification of collected tweets, a Support Vector Classifier (SVC) with TF-IDF features was trained and tested using labelled tweets. The classifier was able to label tweets collected with an accuracy of 77.52%. Location information was retrieved from the tweets classified as complaints using the Stanford Core NLP named entity recognizer. The locations identified in the complaint tweets using the Stanford NER were reverse geocoded using the Google Geocoding API and the resulting geographic coordinates plotted on a static google map. Frequent words in the complaint tweets were represented using a WordCloud. The county government can use this information for decision making, planning and to give feedback to the public on resolution of the same.en_US
dc.description.sponsorshipFaculty of Information Technologyen_US
dc.identifier.urihttp://hdl.handle.net/11071/12053
dc.language.isoen_USen_US
dc.publisherStrathmore Universityen_US
dc.subjectPublic complaintsen_US
dc.subjectSocial mediaen_US
dc.subjectData miningen_US
dc.subjectNatural Language Processingen_US
dc.titleA Public complaints data mining and visualization tool for social media: a case of Nairobi City Countyen_US
dc.typeThesisen_US
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MSIT Theses and Dissertations (2020)