ANALISIS KECENDERUNGAN LAPORAN MASYARAKAT PADA “LAPORGUB..!” PROVINSI JAWA TENGAH MENGGUNAKAN TEXT MINING DENGAN FUZZY C-MEANS CLUSTERING

Effective communication between the government and society is essential to achieve good governance. The government makes an effort to provide a means of public complaints through an online aspiration and complaint service called “LaporGub..!”. To group incoming reports easier, the topic of the report is searched by using clustering. Text Mining is used to convert text data into numeric data so that it can be processed further. Clustering is classified as soft clustering (fuzzy) and hard clustering. Hard clustering will divide data into clusters strictly without any overlapping membership with other clusters. Soft clustering can enter data into several clusters with a certain degree of membership value. Different membership values make fuzzy grouping have more natural results than hard clustering because objects at the boundary between several classes are not forced to fully fit into one class but each object is assigned a degree of membership. Fuzzy c-means has an advantage in terms of having a more precise placement of the cluster center compared to other cluster methods, by improving the cluster center repeatedly. The formation of the best number of clusters is seen based on the maximum silhouette coefficient. Wordcloud is used to determine the dominant topic in each cluster. Word cloud is a form of text data visualization. The results show that the maximum silhouette coefficient value for fuzzy c-means clustering is shown by the three clusters. The first cluster produces a word cloud regarding road conditions as many as 449 reports, the second cluster produces a word cloud regarding covid assistance as many as 964 reports, and the third cluster produces a word cloud regarding farmers fertilizers as many as 176 reports. The topic of the report regarding covid assistance is the cluster with the most number of members.

The Evolution of the Internet and Social Media: A Literature Review

This article reviews and analyses factors impacting the evolution of the internet, the web, and social media channels, charting historic trends and highlight recent technological developments. The review comprised a deep search using electronic journal databases. Articles were chosen according to specific criteria with a group of 34 papers and books selected for complete reading and deep analysis. The 34 elements were analysed and processed using NVIVO 12 Pro, enabling the creation of dimensions and categories, codes and nodes, identifying the most frequent words, cluster analysis of the terms, and creating a word cloud based on each word's frequency. The review presents updated information about technological trends, marketing, and chronological elements regarding the evolution of the internet and social media.

COMMUNICATING FIVE-YEAR BUDGETS FOR THE INDIAN ECONOMY: COMPARATIVE TEXT AND SENTIMENT ANALYSIS

The content on social media is full of useful information that helps in communicating people’s preferences and opinions. The various examples in this context are that people frequently express their opinions about films and other social issues using Twitter, Facebook, etc. In this work, Sentiment Analysis of the Annual Budget for five financial years, namely, 2017–2018, 2018–2019, 2019–2020, 2020–2021, and 2021–2022 was initiated with the help of Twitter. Firstly, the researcher applied Text Mining to extract the budget's text data documents and computed correlation to know the association of influential words. Then, in analysis section plotted the occurrence of the words and the accompanying word cloud. The analysis was performed employing R software. Finally, the sentiment score for each item was calculated and assessed. This research is crucial because conducting a comparative text and Sentiment Analysis of five-year budgets for the Indian economy would communicate the previously prevailing positive and negative forecasts and thinking, which will aid future policymakers in planning future budgets.

Analysis and Mining of Internet Public Opinion Based on LDA Subject Classification

This paper uses Python, R language, Gephi and other software to crawl and classify the comment content of Weibo hot search events. Using word cloud, co-occurrence social network graphs, LDA topic classification visualization methods, this paper regularizes and integrates public opinions of hot events. Through this research, we can get the influence of public opinion mediators, public opinion objects, and government forces on the network public opinion and put forward corresponding improvement suggestions. We hope to contribute to the government’s governance and prevention of online public opinion during the spread of COVID-19 and other public hot events.

Impact of landfill sites on superficial water quality: case of the controlled landfill of Zerizer (N-E Algeria)

Adaptation of environmental literacy awareness to the education system and reflection of interest and attitude towards the environment in behavior is a critical element in order to ensure sustainable development. Turkey's interest in the environment and sustainable development began to increase at the end of the 20th century. Unfortunately, the reflection of this interest in the education system has not been at the desired level. The foremost aim of the study is to measure the level of consciousness and awareness about sustainable development of the students who are in the master's programs of the department of public administration. As a sample, students studying in the relevant field between 2018-2020 at Pamukkale University and Niğde Ömer Halisdemir University Social Sciences Institute were selected. In this study, where the qualitative method was preferred, the data of 20 students who provided feedback to the 11-expression interview form were analyzed using the word cloud method. It was concluded that the participants began to examine the relationship between the environmental factor and sustainable development, understood the importance of sustainable development for future generations, but could not adequately reflect the consciousness and awareness they had achieved in their behavior.

E-Participation Within E-Government

Through a bibliometric approach, this paper presents the results of a systematic review of the literature pertaining to e-participation and e-government. The objective of the review was to map the evolution of the current literature and identify the leading sources of knowledge in terms of the most influential journals, authors, and articles. From a total of 235 relevant articles, selected from the Scopus database, detailed citation analysis was conducted. The analysis of citation data showed that Government Information Quarterly is the leading journal in e-participation research. Lee Jooho was found to be the leading author in this field in terms of a total number of publications, total citations, and h-index, while the most cited article was authored by Vicente and Novo in 2014. The study further explored the conceptual structures such as word cloud, word dynamic trends, co-word analysis, and bibliometric coupling to show the trends. The contribution of this study is to clearly outline the current state of knowledge regarding e-participation and e-government services in the literature.

What Indian working class is saying about the COVID-19 pandemic: concerns and reactions

This is an exploratory research highlighting the concerns and reactions of Indian working-class people towards the COVID-19. It was observed that most of the Indian working-class people were seriously concerned about the pandemic and responded well to the measures suggested by the Governments and other agencies in a big way. Most of the respondents believed the pandemic will be effectively controlled across the globe within one year. Word cloud and other data visualization techniques were used to analyze the reactions of the Indian working class towards the Central and State government’s initiatives to contain COVID-19. In the word cloud of the top 150 popular words for both central and state governments Lockdown, People and Government have taken the central stage. The word streaming analysis suggests the intense relationship among the most frequent words in the dataset. For the central government, it was social distancing and for state government, it was social distancing and relationship between central and state governments. The sentiment analysis for both central and state government was neutral, mostly. The researchers are of the view that the research will provide a deeper insight into human perception and behavior towards the measures initiated by the Central and State Governments in any similar difficult situations. Further the concerns identified may be taken into consideration by the Government while designing the policy measures and other interventions by the Government.