Visualising the Impact of the legislation by analysing public DIscussions using statistical means (no: EP-08-01-014)
Policy development can be considered in many respects as an innovation process, where there is a need to initiate ideas, collect evidence for and against the ideas and finally develop a workable policy. This process requires considerable discussion with businesses, NGOs and civil society to ensure that both experts in the subject domain can provide input and also that those that might be affected by the resulting policy have an opportunity to provide evidence. There is a need to ensure that knowledge collected through online discussions is appropriately identified, represented and shared. However, although online consultations through discussion forums are typically moderated, any analysis is typically left to after the consultation period in terms of performing various statistics on the total number of contributors, total number of posts, the most active contributors and the most popular posts. Although these are interesting metrics, they do not enhance the conversation or provide potential users with real insight into the topic under discussion. Therefore such analysis is not available in a manner that would ease navigation, comprehension, and understanding the social interaction. What is needed is an analysis that has the potential to support users to have more informed discussion and to support government to better understand the emerging arguments and ideas contributing to the policy.
In order to resolve this problem, various visualization techniques can be applied to make knowledge emerging through the on-line discussion more explicit. Proper visualization metaphors have the ability to support the users in improving their ability to process large and complication information spaces. Such techniques include visualization of both quantitative and qualitative data within and about the discussion. The visualization can show which topics are popular and how the interest changes in the time, i.e. how do they evolve over time. Moreover, such an analysis can show what people like and what dislike regarding the topics they are discussing about (a kind of sentiment analysis). The main advantage of the visualization is that it enables a multidimensional view on a discussion and not one-dimensional interpretation of its results. For example, instead of having a statistically-based statement that 60% of citizens support legislation draft in an on-line discussion forum, a proper visualization of this discussion can show how and why it happened. Further, it can show that at the beginning of the discussion 85% people supported the draft (related to ”how” question), but after introducing the issue of the climate protection, the number of supporter decreased relatively to opponents (related to “why” question). In other words, the role of discussion analyses is not only to support policy making process with the public opinion in terms of “citizens like it” or “citizens dislike it”, but rather to explore the “why” and “how” (beside “what”) in the public opinion. This process has two important implications:
1) Policy makers can not only hear (what), but also understand (how, why) public opinion, which leads to a better understanding of the impact of the legislation
2) Citizens can not only express (what) but also efficiently explain their opinion, by using the current context of the discussion (how, why), which leads to their more active/detailed involvement in the participatory legislative process, which again leads to the better understanding of the impact of a legislation
Therefore, the main goal of the visualization is to support various types of analyses which can explore the long tail of the discussions, i.e. the information hidden between “big” arguments, which in fact contributes enormously to understanding the public opinion. Additionally, statistics of these analyses plays an important role in assessing the costs and benefits of proposed or adopted legislation.
Current tools for the visualization miss this opportunity, especially the explicit link between the discussions related to legislation and their impact on this legislation. The main challenge of VIDI proposal is to close this gap, as presented in Figure 1.
Figure 1. Closing the policy making loop: Policy makers create some legislations, which are consumed by citizens, who express their opinion through participating in various discussions forums. VIDI platform takes data from discussions, analyzes and visualizes it, returning to the policy makers the public opinion about the legislation. In the same time VIDI platform gives the context about current discussions to the citizens, that provokes their more active involvement
VIDI represents a very innovative technological solution, based on the powerful combination of the linguistic and statistic analysis of the text documents (discussions) in order to extract information from them, known as Text Mining, which enables further, extensive, sentiment-based analyses of the discussions, known as Opinion Mining, inclusive estimating their impact on the legislation and the “cost” of implementing the legislation. We use novel visualization techniques for presenting different views on the information and enabling efficient navigation through this large information space. In particular, VIDI will provide an efficient toolset for an advance visualization of messages posted in an on-line discussion forum, that will support „monitoring“ and analyzing discussions. The ultimate goal is a better understanding of emerging arguments and ideas contributing to the policy making process.
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