Historically, online data has provided meaningful insights for information mining, leading to the adoption of knowledge graphs for application to online data. Knowledge embedding has become an important aspect of encoding and decoding links, relationships, and predicting the ties of an entity to an existing knowledge graph. This study applied topic modeling to extract topics, entities, and themes from heterogeneous web data from different sources around the Indo-Pacific region and modeled a knowledge graph. The knowledge graph was subjected to knowledge embedding by applying four scoring mechanisms: ComplEx, TransE, DistMult, and HolE, on a domain knowledge graph of Indo-Pacific Belt and Road initiatives to determine whether it was capable of revealing missing insights. This work significantly uses knowledge graphs and embedding to understand socioeconomic-related discussions online. Valuable insights were gained from the data in this research's clustering results of knowledge embedding. Important themes such as NASAKOM and BRI were identified in Cluster 0. Cluster 1 contained themes that discussed Marxist movements synonymous with Indonesia, and Cluster 2 showed themes on China's road policies, such as Asia-Pacific Economic Cooperation and Export-Import Bank China. Cluster 3 focused mainly on China's economic policies and the Philippines. Overall, this study demonstrates the usefulness of topic modeling and knowledge embedding in uncovering insights from online data and has implications for understanding socioeconomic trends in the Indo-Pacific region.

The advent of web 2.0 and social media blogging has enabled researchers to have access to troves of blog data in the 21stcentury. While platforms and big corporations like Twitter and Facebook can apply the concept of user networks by leveraging internal tools developed by their teams. Researchers and analysts have had to make use of repetitive ways of analyzing blog networks for collected data. This is due to the limited live databases to store and keep track of blog data and the lack of centralized publicly available tools with such capability. When analyzing blog data, the analyst often wants the capability to model relationships and see blogs that share ideological similarities. This is so because blogs always reference each other when they share similarities in content or when they attempt to reinforce a point of view discussed on the medium. Since the blogosphere is made up of a virtual network of blogs - the blogosphere is defined as the network of blogs and has no limitation in blogs referencing one another. It becomes imperative to have a solution that can allow an analyst to visualize the relationships between blogs based on how influential these blogs are when the analyst tracks the discus on the blogs. We address this by providing users with the capability to visualize and analyze blogs that are influential and how connected these blogs are by a way of network visualization. This demonstration shows how the BlogTracker application analyze and visualizes the blog network.

Blogging has become an essential part of the new print media of the 21st century despite the emergence of social media platforms like Twitter and Facebook, with many news agencies, media outlets, journalists and users using this medium to write without any restriction on topics of choice or events that happen over the world. Although social networking sites have also become a hotbed where users share their views, it suffers from distraction when users try to air their views on topics that affect them due to character limitation, real-time toxic behavior, and content ownership rights. Social networking sites like Facebook, Twitter and Reddit are sometimes used to drive traffic to blogs sites. The blogosphere, defined as the network of blogs, is growing at an exponential rate. Medium.com and WordPress.com are among the top blogging platforms, with WordPress leading the way as a top blogging platform and followed by other platforms like Medium, Hashnode, Tumblr, and blogger. Analyzing blog data helps understand the pulse of a society, know what resonates with a community, and recognize the grievances of a group, among other reasons. Since there is no character limit in blogs, unlike Twitter, blogs allow much depth in discourse, allowing it to be an effective platform for setting narratives. Blogs also provide a convenient platform to develop situational awareness during a socio-political crisis or humanitarian crisis in a conflict-torn region or a disaster-struck area. To address the difficulty of having a publicly accessible blog data analytical solution since solutions like Blogdex, among others, were either discontinued or made proprietary, we present BlogTracker. This tool helps users analyze public discussions with real-time data update capability and analyze narratives and emotion distribution on associated blog posts and trackers. This demonstration shows how the BlogTracker application analyses blog data with a case study about COVID-19.