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'''An Audience Study on the Data Visualizations of Online News Regarding the Pork Barrel Scam in 2013-2014'''

ABSTRACT:

Uy, D. (2015). An Audience Study on the Data Visualizations of Online News Regarding the Pork Barrel Scam in 2013-2014, Unpublished Undergraduate Thesis, University of the Philippines Diliman.
	
The research was an exploratory study on how data visualizations affect the audiences when they read online news articles about the 2013-2014 Pork Barrel Scam.
It sought to assess whether or not using data visualizations was is effective in clarifying data about Priority Development Assistance Fund (PDAF).

The main objective was to discover if students from the University of the Philippines Diliman were willing to take the time to further read and dig deeper on national issues after viewing data visualizations that had already been angled and framed by new organizations. Specific objectives include determining the users’ expectations and perceived ease of use of online news, analyzing their attitude toward using online data visualizations, analyzing their actual use / behavior in using online news, determining whether the presence of data visualizations in the stories related to the Pork Barrel / PDAF Scam in the year 2013-2014 encourage or discourage further reading of news articles about the issue, and finally, finding out if the readers of online news regarding the PDAF Scam even look at the data visualizations provided.

Results of the study suggest that data visualizations do encourage further reading of news articles, but that the respondents do not regard that data visualizations are an integral story-telling and data-rich medium.

View Thesis:<br/>
[https://iskomunidad.upd.edu.ph/images/2/28/An_Audience_Study_on_the_Data_Visualizations_of_Online_News_Regarding_the_Pork_Barrel_Scam_in_2013-2014.pdf In PDF Format]

[https://iskomunidad.upd.edu.ph/flipbook/viewer/?fb=2011-14074-An-Audie#page-1 In Flipbook Format]

[[Category:Theses]][[Category:CMC Thesis]][[Category:Department of Journalism Thesis]][[Category:2016 Thesis]][[Category:Thesis--Data Journalism]][[Category:Thesis--Data Visualizations]]