• Asian Journal for Public Opinion Research
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• v.6 no.1
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• pp.31-38
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• 2018

Leading up to the 2019 presidential election in Indonesia, campaigns have emerged through social media, particularly Twitter, using various hashtags, such as #2019GantiPresiden (2019 Change President) and #TetapJokowi (Always Jokowi). This paper tries to understand the presidential candidates' power map in forming opinions and influencing voter behavior by analyzing Twitter from August 6, 2018 to September 15, 2018, just before the beginning of the official campaign period, by searching for the keyword "pemilihan presiden RI Tahun 2019" (RI presidential election in 2019). According to our NodeXL's analysis, there were 1,650 active Twitter users talking about the 2019 presidential election. The 1,650 Twitter users have formed a communication network of 46,750 relationships formed from messages in the form of tweets, comments, and retweets. Our analysis found that those mentioning "pilihan presiden 2019" form large communication networks around four clusters: one for each of the two candidates (Jokowi and Prabowo) and two for opinion leaders who are undecided about the election (Gus Mus and Mas Piyu). GusMus is a religious leader, as an official of the PBNU Rais Syuriah (an Islamic organization) and has a large following both on and off Twitter. "MasPiyu" is an unidentified Twitter user; he only has a large following on Twitter, but does not have support offline.

• Journal of Industrial Technology
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• v.17
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• pp.43-50
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• 1997

Local administration is closely related with intention of residents. Especially, a plan item is closely related with life of residents. Therefore, it has to be logical and objective solution for opinion convergence. Decision of opinion has to be in a triangular position standard and stand in a trio of criteria in standard. But, opinion convergence of residents very difficult. Recently, the technique of GIS presents method for oponion convergence with logical and objective and scientifically solution. And, this study present method for decision of intention to a complex element with GRID and NETWORK techniques of GIS. This study present optimun site of constructure with the GIS technique in consideration of a side face of transportation, technical, social economy and environments.

• Asian Journal for Public Opinion Research
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• v.8 no.3
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• pp.393-406
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• 2020

The discourse on the lockdown in Indonesia is getting stronger due to the increasing number of positive cases of the coronavirus and the death rate. As of August 12, 2020, the confirmed number of COVID-19 cases in Indonesia reached 130,718. There were 85,798 victims who have recovered and 5,903 who have died. Data show a significant increase in cases of COVID-19 every day. For this reason, there needs to be an evaluation of the government policy of the Republic of Indonesia in dealing with the COVID-19 pandemic in Indonesia. An evaluation of policies for handling the pandemic must include public opinion to determine any weaknesses of this policy. The development of public opinion about the lockdown policy can be understood through social media. During the COVID-19 pandemic, measuring public opinion through traditional methods (surveys) was difficult. For this reason, we utilized big data on social media as research data. The main purpose of this study is to understand public opinion on the lockdown policy in overcoming the COVID-19 pandemic in Indonesia. The things observed included: volume of Twitter users, top influencers, top tweets, and communication networks between Twitter users. For the methodological development of future public opinion research, the researchers outline the obstacles faced in researching public opinion based on big data from Twitter. The research results show that the lockdown policy is an interesting issue, as evidenced by the number of active users (79,502) forming 133,209 networks. Posts about the lockdown on Twitter continued to increase after the implementation of the lockdown policy on April 10, 2020. The lockdown policy has caused various reactions, seen from the word analysis showing 14.8% positive sentiment, 17.5% negative, and 67.67% non-categorized words. Sources of information who have played the roles of top influencers regarding the lockdown policy include: Jokowi (the president of the Republic of Indonesia), online media, television media, government departments, and governors. Based on the analysis of the network structure, it shows that Jokowi has a central role in controlling the lockdown policy. Several challenges were found in this study: 1) choosing keywords for downloading data, 2) categorizing words containing public opinion sentiment, and 3) determining the sample size.

• The Journal of the Korea Contents Association
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• v.20 no.8
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• pp.19-33
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• 2020

This study aims to analyze on the changes of opinion in terms of Sejong City construction using big data. The research data are newspaper articles related to the argument of construction in Sejong City. The newspaper article data was reported by Hankyoreh, Dong-A Ilbo and Hankook Ilbo. The arguments related to the construction of Sejong City was included the new administrative capita, multifunctional administrative city and amendments of Sejong City. The analysis method used in this study is frequency analysis, sentiment analysis and social network analysis using python and gephi 0.9.2 programs. The results of the analysis are as follows. First, as a result of frequency analysis, the keywords of Hankyoreh showed the characteristics of consent - consent - dissent according to the construction period of Sejong City. The Dong-A Ilbo showed positions of dissent - dissent - consent. In addition, the Hankook Ilbo was analyzed to have the characteristics of dissent - consent - dissent tendency. Secondly, results of sentiment analysis, The Hankyoreh showed positive - positive - negative tone. The characteristic of Dong-A Ilbo is that the focus has changed from negative to negative to positive. The Hankook Ilbo showed that changed from negative to positive to negative. Finally, the results of social network analysis are as follows. At the time of the construction of Sejong City, each opinion of media was showed a changes in issues according to political and ideological characteristics such as conservative, progressive and moderation. In detail, Hankyoreh focused on balanced regional development. The Dong-A Ilbo represented the opinion of the Conservative Party. The Hankook Ilbo was highlighting the issues confronting the conservative party and progressive party during the construction of Sejong City.

• Journal of Digital Convergence
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• v.12 no.8
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• pp.67-76
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• 2014

In this study, we investigated opinion leaders' communication activities on Facebook and analyzed the differences of communication patterns on Facebook between Korean and US college students. As a primary source of information, we conducted an online survey to collect data from students currently enrolled at two different universities in US. Additionally, we utilized online survey data previously collected from Korean students. According to our analysis, we found that US male students had more active opinion leadership than Korean male students. Also, opinion leadership of Korean students' was significantly associated with both active and passive communication patterns on Facebook whereas opinion leadership of US students' was significantly associated with passive communication patterns.

• Journal of Digital Convergence
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• v.11 no.5
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• pp.41-51
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• 2013

A lots of social data are distributed, utilized and opened through the social media. They have characterized effectiveness and pleasure of information to the media by social data but it is ignored about excessive exposure of information and damage from collective reply of personal attack type. In this paper, we study about analysis of opinion social data on the SNS (Social Network Service) by analyzing of collective damage reply. It is analysed by diverse measurement method for distribution and disuse of the amount of Buzz data that is analysed data from structured social network.

• The Journal of the Korea Contents Association
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• v.10 no.11
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• pp.30-37
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• 2010

It is very important to analyze online customer reviews, which are small documents of writing opinions or experiences about products or services, for both customers and companies because the customers can get good informations and the companies can establish good marketing strategies. In this paper, we did not propose only dependency network model which is tool for analyzing online customer reviews, but also designed and implemented the system based on the dependency network model. The dependency network model analyzes both subjective and objective sentences, so that it can represent relative importance and relationship between the nouns in the sentences. In the result of implementing, we recognized that relative importance and relationship between the features of products or services, which can not be mined by opinion mining, can be represented by the dependency network model.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.3
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• pp.239-246
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• 2013

The IEEE 802.15.4 offers standard about PHY and MAC layer and features low power, low bandwidth, and low speed data communication. Because of this reason, IEEE 802.15.4 is only within a limited range such as sensor detection and home network; nevertheless, the research about transmission multimedia data like voice packet through wireless sensor networks is conducted widely. In this paper, we proposed the group communication system based on the sensor network. TDMA/TDD MAC based on the IEEE 802.15.4 PHY for voice communication on the sensor network is designed by improvement existing peer-to-peer voice communication on the sensor network and hardware is implemented for group communication. To measure the quality of designed system, mean opinion score (MOS) is obtained from the experiment and verified by using sine wave method. As a result of an experiment, we expect that a many cases of application solution can be developed using presented system.

• The Korean Journal of Community Living Science
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• v.27 no.spc
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• pp.665-679
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• 2016

This study examined the main factors for activating rural tourism of Jeollabuk-do using big data analysis. The tourism big data was gathered from public open data sources and social network services (SNS), and the analysis tools, 'Opinion Mining', 'Text Mining', and 'Social Network Analysis(SNA)' were used. The opinion mining and text mining analysis identified the key local contents of the 14 areas of Jeollabuk-do and the evaluations of customers on rural tourism. Social network analysis detected the relationships between their contents and determined the importance of the contents. The results of this research showed that each location in Jeollabuk-do had their specific contents attracting visitors and the number of contents affected the scale of tourists. In addition, the number of visitors might be large when their tourism contents were strongly correlated with the other contents. Hence, strong connections among their contents are a point to activate rural tourism. Social network analysis divided the contents into several clusters and derived the eigenvector centralities of the content nodes implying the importance of them in the network. Tourism was active when the nodes at high value of the eigenvector centrality were distributed evenly in every cluster; however the results were contrary when the nodes were located in a few clusters. This study suggests an action plan to extend rural tourism that develop valuable contents and connect the content clusters properly.

• The Journal of the Acoustical Society of Korea
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• v.39 no.4
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• pp.292-302
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• 2020

Machine learning algorithms have made immense contributions in various fields including sonar and radar applications. Recently developed Cycle-Consistency Generative Adversarial Network (CycleGAN), a variant of GAN has been successfully used for unpaired image-to-image translation. We present a modified CycleGAN for translation of underwater ship engine sounds with high perceptual quality. The proposed network is composed of an improved generator model trained to translate underwater audio from one vessel type to other, an improved discriminator to identify the data as real or fake and a modified cycle-consistency loss function. The quantitative and qualitative analysis of the proposed CycleGAN are performed on publicly available underwater dataset ShipsEar by evaluating and comparing Mel-cepstral distortion, pitch contour matching, nearest neighbor comparison and mean opinion score with existing algorithms. The analysis results of the proposed network demonstrate the effectiveness of the proposed network.