Blog post
December 9, 2020

The regional comprehensive economic partnership through the eyes of AI

The media coverage of the regional comprehensive economic partnership (RCEP), a monumental deal among 15 Asia Pacific countries, has been interesting.

As media analysts, we looked into more than 800 articles and videos from the prominent news outlets across the 15 countries that signed the deal within the time period of 8 November to 20 November 2020.

Natural language processing uncovering the power dynamics in the region

We employed state of the art AI models specialising in natural language processing (NLP), and contextualised them with our strategic viewpoint.

Sharing more about the AI analysis, Joseff Ymanuel Tan, Jr, data scientist at Isentia, noted: “NLP models work well for key information retrieval, specifically identifying proper nouns (entities). The entities are classified into several categories by the AI/NLP model.”

The first category we were interested in was the most frequently mentioned location names (country names, city names, etc). The image below provides a glimpse of the NLP model identifying the entities from an excerpt of an article.
The word cloud here shows the countries identified by the AI/NLP model. The bigger the country name is, the more number of articles covered it. The US (appeared in 843 articles) & China (749 articles) were the top countries mentioned.

Sharing insights from the NLP analysis, Arisa Otsuka, Analyst at Isentia, said, “This deal was seen as a significant victory for China as it reduces the impact of the ensuing trade war between the US and China by reducing China’s reliance on US trade [1]. The articles also mentioned the waning influence of the US as many allies rethinking their economic ties with the US [2].”

One of those US allies being Japan (584) which was also the third most mentioned country. Some of the reasons why Japan was mentioned where their plan to sign military ties with Australia [3]; also Japan was covered as the one ensuring the protection of their local farmers by retaining tariffs on essential products like rice, wheat, dairy etc.[4]

Arun Elangovan, Regional Analytics Manager of Isentia Asia said, “At first glance of the country names, the AI is merely confirming the hypothesis that everyone would have regarding this deal, the 15 countries who signed the agreement are covered equally. But when we look at the results of the AI through a different lens, the message changes.”

While the previous word cloud shows how many articles the countries appeared in, the following word cloud demonstrates how many times the countries were mentioned across articles. This word cloud not only captures the essence of how prominently a country is covered but also uncovers subliminal messages or in other words, the unsaid.

The articles more prominently mentioned China (4324 times) than any other country. US (2171 times), Japan (1483) and Australia (1246) were some of the other countries also prominently mentioned. This could seed the idea that some countries are more influential than others, portraying the power dynamics in the region.

The media also extensively covered some countries that were not part of the deal. The first one being India (296 articles), as India was initially part of the RCEP and withdrew towards the end of last year. The coverage on India was mostly about how the countries (esp. Australia, Singapore & Vietnam) [5][6] are hopeful & keeping the door open for India to join the partnership in the future. Japan considers India’s presence necessary to counter China’s economic weight [7]. The other country was Taiwan (66 articles). Taiwan was reportedly underplaying the significance of RCEP by pointing out that 70% of it’s exports to RCEP is already tariff-free; instead, they were hopeful of joining the Trans-pacific Partnership (CPTPP).[8]

Video AI hints towards a hopeful & prosperous future

The subliminal messaging in video coverage are less subtle as compared to articles. This is due to a video having 2 components, the visuals and the audio/speech.

“Most of the news reporting on mainstream media state the facts through the audio/speech and show accompanying visuals. When we analysed the audio/speech, the narratives were very similar to the one we uncovered through the articles,” said Ma. Angelica Tatad, Data Scientist at Isentia.

But while analysing the visuals we found different narratives. Francis De Leon, Jr. Data Scientist at Isentia said the analysis of the video was “done through a state of the art neural network (AI) which can identify the objects shown in a video. Our analysts then group these object labels into relevant categories.”

Apart from the usual suspects with groups of objects detected like people (incl. audience, speaker, journalist etc.) & event-related labels (incl. conference, auditorium etc.).

The above image shows the AI (Google Video AI) identifying various objects shown in a video.

There were some interesting group of objects detected such as Buildings & Cityscape.

The above graph shows the various labels and the number of times they appeared in the videos.
The other group was Transport & Vehicles (as shown in above graph)

These groups of labels seem to indicate that the media is visually portraying this partnership as future-looking and opportunity for progress.

The other group of labels that were informative was the Food group (as shown in above graph)

The media also showed various parts of the food supply chain, touching on one of the top priorities for countries especially in the Southeast Asia region, food security. This deal brings could potentially ease the tariffs on food import and export amongst the countries that are part of the deal.

Analysing the coverage around RCEP through the eyes of the AI revealed that the media while largely emphasising the impact on the on-going power dynamics be it the dynamics between the US & its allies and China, also portrayed this deal as bringing a bright and prosperous future to the countries in the region. It also revealed that there are some subtle/subliminal messages that lie underneath the obvious.

Written by: Arun Elangovan, Regional Manager, Advance Analytics – Insights, Asia

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The advent of LLMs and AI search means that there has been a colossal shift in how audiences are consuming information today,  and a reciprocal shift in how all types of organisations, from government agencies to brands are responding . But while discussion amongst PR and comms pros tends to fall disproportionately on how brands are impacted, the needs of the former are just as keenly felt, and often quite distinctive.

So how can government agencies respond, especially in a time of global flux, when major policy changes need to be communicated and important stakeholders need to be managed? After all, government organisations do care about reputation, much as brands do, but have quite distinctive goals when it comes to ensuring accurate information reaches the right audiences.

There is a new entry point for stakeholders


The era of "Let me Google that" is rapidly fading. Instead of clicking through to official websites, people are asking chatbots for direct answers.  What’s striking is that government agencies often have no visibility on how they’re being talked about in the LLM space, even as it becomes a central channel for messaging and reputation. 

When AI models become the primary gatekeeper, audiences bypass official portals entirely — driving down site traffic and leaving agencies vulnerable to misinformation, negative sentiment, or worse, being left out of the conversation altogether. 

Therefore, the entry point is different. For commercial brands, this shift is profound but in some ways mediated – an FMCG brand, for instance, often discovered through third-party platforms in any case. But for government entities, the stakes are entirely different. As the sole, authoritative source for public information, they need citizens on their websites to get accurate details. Government agencies, especially if they are the authority or regulator in a particular industry or sector, need to make sure audiences know where to go to get the right information.

Different types of government agencies have different considerations

Not all government agencies are alike, and they all have different parameters that are quite non-negotiable for them, just by the way they function. 

  1. Service delivery agencies - these rely heavily on content freshness. They can’t risk outdated sources impacting eligibility or process changes not reaching audiences.
  2. Regulators - these need to transmit authority and trust. Regulators have to make it a priority that they’re amongst the first place audiences go to for information and that the industry they’re regulating does not put them in the shade on the channels stakeholders are actually using
  3. Policy departments - did the AI's account of a policy match what was actually announced? They want to be able to make sure the accuracy of a policy (and ideally, its effectiveness) is translated when audiences search through LLMs.
  4. Local and state authorities want to make sure the services they carry out on behalf of locals are visible too. Much like service providers, there is a question around access and awareness of programmes and regulations, but also an added consideration: not appearing on LLMs discontent amongst those wishing to see a return on taxation and electoral mandates, and give credence to bad actors.

What do government agencies want to get out of this new LLM-mediated landscape? 

Reputation is important, but that exists downstream from maintaining a flow of accurate information. It’s useful for communications teams in government organisations to self reflect and ask themselves the following questions:

  • Where are citizens going to find information about your services if not your website — and do you know what they're being told?
  • If there was a significant policy change or incident in the last twelve months, do you know how it's currently being characterised when someone asks an Al tool about your agency?
  • When you communicate a major service change or policy update, do you have any way of measuring whether it’s surfacing in searches about you?
  • How do you currently understand the gap between what your agency publishes and what citizens actually receive when they search for information?
  • Are there community groups, advocacy organisations, or media outlets shaping perception of your agency - and do you know if that's feeding into what Al models say?

These are gaps they already realise, but they don’t actually know what to do about it – how to manage or measure them. They need a tool that allows them to know this critical piece of information and make informed decisions. 

Lumina AI View: AI visibility for PR & Comms


Lumina AI view is built for communicators who want to understand how their organisation and their competitors are being talked about by various AI models – including ChatGPT, Gemini, and Claude. AI View users get an insight into which sources are being cited, and how they would need to respond as a way of protecting their reputation or making sure correct information about them is being disseminated. 

The tool provides an AI view score — a composite metric ranging from zero to 100, designed to help track brand performance over time and facilitate comparisons against competitors. It is calculated using five weighted factors — sentiment, visibility, authority, dominance and freshness. Beyond the overall score, the platform provides a summary of a brand's AI narrative based on four distinct reputation pillars — direction, performance, integrity and innovation. 

These pillars help users identify exactly which dimension of a brand's reputation is under pressure, offering specific, actionable insights for board presentations or reviews. Ultimately, while the AI view platform provides the necessary intelligence, the strategic decisions regarding how to respond to these insights remain with the organisation.

Spotlight: An Australian Council


This progressive local government council is located in Australia’s leading center for culture and sports.

The council earned an AI view score of 74 reflected by strong reach and authority. Publications like CBD News and its own website are the most cited by LLMs — interestingly, most of them being cited by Claude.

Content freshness scored lower at 48. Their website still carries error pages and annual reports from a few years ago. If a report — one that is seen as an organisation’s most comprehensive and authoritative content, is still being cited even if it’s older, might potentially be in the way of the organisation’s own perception. Which means more work is needed to prevent outdated content from still appearing.

What type of content is showing up?

Most citations for the council originate from government sources, followed by news outlets, reports, and blogs. The domain is evenly split between owned content and content earned from external sources media articles and independent authorities. 

While most are recent, some older articles from major outlets such as The BBC remain visible and may significantly influence how LLMs perceive the council. Owned content typically addresses last year’s budget plans and the council’s latest vision for the city, which LLMs are referencing. Government sources are the major content type, however, external sources have a greater impact on the council’s overall LLM score.

The stakes are higher for government agencies

When brands track LLM visibility, they often ask, "Are we shown in a positive light?" or "Are we cited accurately?" For the government, additional questions arise: "Is this information accurate enough for someone to act on?" and "Are we still viewed as more authoritative than what we oversee?" Mistakes can have serious consequences, such as individuals applying for ineligible programs or missing critical deadlines for new initiatives or elections. This can quickly lead to public frustration. It is essential for government communicators to recognize these risks.


If you would like to know more about our Lumina suite, please reach out here and our team will get in touch with for you a quick demo.

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Blog
Why is tracking government visibility on LLMs different from tracking brands?

Government agencies often can’t see how AI chatbots describe them. Here’s why LLM visibility matters and how to track it.

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There is a new frontier where public perception is shaped: Large Language Models. Right now, LLMs are answering critical questions about your organisation. What are they saying? And more importantly, which sources are shaping those answers?

To navigate this landscape, public relations professionals don't need generic tools, but rather technology that speaks their language, and addresses the realities of a changed media and informational landscape.

That is why we're unveiling Lumina AI View, the latest addition to our intelligent suite of AI tools from Isentia. Trained specifically on the workflows and challenges of modern PR & communications, Lumina AI View helps you understand exactly what AI knows about you, and how it learned it.

A new standard for AI visibility

AI View tracks your citation strength and source quality alongside those of your competitors, giving you a clear view of where you hold authority and where you have gaps.

Lumina AI View maps your AI reputation from the ground up, allowing you to:

  • See which sources matter: When tools such as ChatGPT or Gemini discuss your organisation, which outlets do they cite? Track your source footprint over time and view the impact of key target media on how you’re discussed. We measure your citation strength and source quality alongside those of competitors, giving you a clear view of where you have authority and where you have gaps.
  • Gain industry-specific insight: Your competitors get cited from Financial Times and Bloomberg. You get cited on Reddit. Each brings opportunity – and risk. Discover how you measure up against industry standards, and target the sources that actually influence how AI represents you.
  • Catch narrative shifts early: AI responses change when new sources appear, sentiment shifts, or old controversies resurface. Get alerts when citation patterns change suddenly, before they impact the way you’re perceived by stakeholders.

Measure your progress: From media monitoring to full media intelligence

Lumina AI View is built on the principle that insights get stronger with repeated measurement. To help you maintain a clear view of your reputation, our proprietary scoring system provides regular updates that show you:

  • Evolving trends in how sources cite your organisation
  • Competitive standing and benchmark metrics
  • Where models differ in information presented, and sources cited 

Whether you run it weekly, on-demand, or whenever you need a check-in, patterns will emerge, trends will become clear, and you will build a baseline that makes any sudden narrative changes both comprehensible and the prerequisite to action.

Lumina AI View is part of Lumina AI, a comprehensive suite of AI tools built specifically for communicators. Our Lumina suite evolves traditional media monitoring into narrative intelligence, enabling you to truly understand how perceptions form, evolve, and impact your reputation.


Get in touch to register your interest and see what Lumina AI View can do for you.

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Blog
Introducing Lumina AI View: AI Visibility Built for PR & Comms

Lumina AI View, the latest in Isentia’s AI suite, is trained on PR & comms workflows to help you understand what AI knows about you — and how it learned it.

Ready to get started?

Get in touch or request a demo.