More changes to social media API’s, the latest from Instagram
It’s been a whirlwind year trying to keep up with the various changes made by social media platforms – especially for professional communicators, developers, agencies, and brands.
At the same time as understanding and usage of the term ‘API’ has accelerated across offices worldwide, social media platforms have begun to restrict access to their application programming interfaces (APIs). With implications ranging from global politics to individual user privacy, that trend is showing no signs of stopping.
API changes have been introduced in order to reduce risks around data privacy, security concerns for users and stamping out improper use of user data.
Most of the changes can be categorised as:
How often and how much data can be requested (rate limit reductions); and
Type of data available (restrictions on user-identifiable data)
Generally, these are positive changes for the whole ecosystem. Users can be reassured at an individual level that there are more controls in place and consideration given to matters of privacy and the prevention of misuse. Facebook’s ‘Here Together’ video, released in the aftermath of the Cambridge Analytica data breach, reflects some of this desired messaging and the drives for these changes.
The latest changes have come from Instagram and more are set to be introduced on 11 Dec 2018.
Here’s how the changes impact the three types of Instagram analysis:
Owned media (for your brands’ own Instagram accounts): Better data on your owned Instagram profiles, but they need to be Instagram business profiles and you have to authenticate to access this data.
Public accounts (for other brands or influencer’s channels): This use case no longer exists for Instagram – there is no longer any data available for public Instagram accounts you don’t own.
Listening: Public hashtag listening on Instagram is no longer supported. Brands will need to move to brand mentions, photo tags and related hashtags.
These may not be the last of the changes, but they are necessary growing pains to regain user trust and provide higher quality authentic engagements. For small businesses and influencers these changes are fairly straightforward – however for those looking to manage communications or marketing strategies they present new challenges in order to stay informed.
These changes apply across the board so all API users will need to jump the same hoops and prove that both privacy measures are met and use of data is acceptable. If you’re interested, you can learn more about the official changes from Instagram read on here.
Loren is an experienced marketing professional who translates data and insights using Isentia solutions into trends and research, bringing clients closer to the benefits of audience intelligence. Loren thrives on introducing the groundbreaking ways in which data and insights can help a brand or organisation, enabling them to exceed their strategic objectives and goals.
With more than 1 billion users on Facebook, and millions more active on sites such as YouTube and Twitter, it has become obvious that social media is an important platform for businesses.
Connecting with the huge variety of consumers already on these sites can open up significant opportunities for marketing and lead generation. Additionally, social media monitoring provides insight and understanding into how your industry, audience and competitors are reacting to market trends and products.
As well as giving businesses and consumers a platform to share their thoughts and participate in ongoing conversations, social media is also a channel through which many people access news stories and important information.
A recent study from Pew Research found that 64 per cent of adults are active on Facebook, and 30 per cent are using the site to receive news. This means that approximately half of the people using Facebook trust the site to deliver their news.
Similarly, 16 per cent of US adults are active on Twitter, with exactly half of those (8 per cent) accessing the news through tweets.
Not only are users reading news on social media, but they are also participating in the sharing and telling of stories. Half of all social network users have shared news stories on their own profiles and a further 46 per cent have discussed news on social media.
However, while social networking sites are a popular media through which to access news, Pew Research found that users on these sites spend significantly less time engaging with the news they read.
Readers who visit news stories directly through a provider's website spend an average of 4 minutes and 36 seconds on each page. In comparison, those who arrive through a link on Facebook spend just 1 minute 41 seconds reading the page.
This shows that while news is being shared and read on social media sites, engagement is significantly greater when consumers go out of their way to access the stories.
"
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Blog
Is Social Media A Good Source For News?
With more than 1 billion users on Facebook, and millions more active on sites such as YouTube and Twitter, it has become obvious that social media is an important platform for businesses.
In the wake of the Facebook Cambridge Analytica scandal, there have been a myriad of changes impacting users of Facebook and Instagram content recently. These changes were made without any notice and were effective immediately which has impacted third-party apps worldwide.
Albeit the speed in which the changes have been made is likely to have been partly driven by the pressure to tighten data practices and potentially align certain timing as CEO Mark Zuckerberg prepares to testify before Congress next week to answer questions about the company’s privacy and data policies.From the perspective of everyday users accessing the content you know and love via the Facebook and Instagram apps will see little to no change. For developers like us on the other hand, the impacts are significant and are only a hint of what is yet to come.In case you missed it, the changes made have been many and impact all third-party apps, whether legitimate or not.
Given the changes have been quick, varied and came without prior notification, we’ve pulled together a quick summary of a few that left developers and other third-party content users of these content feeds frustrated:
Instagram have removed 17 ways of accessing content
This means something as simple as code to access recent posts of a public company, suddenly stopped working. Quick changes had to be made to use alternative methods.
Facebook & Instagram have removed access to many fields
Fields like how many followers a user has, or how many posts you have made, but many more have gone.
25x drop in Instagram content
The Instagram API restricted the flow of content by 25x, meaning that public posts previously being collected has been reduced significantly, requiring different approaches to be taken that are more efficient.
These are only a few of the changes that have happened with more expect in future. With CTO Mike Schroepfer commenting that they will lock down access, review previously allowed apps, and then hand out access to the apps that deserve it.
While this is promising from the perspective that Facebook is taking action to breath some confidence back into their data practices, it will still be interesting to see how they now start to crack down on third-party apps that are using and abusing content. With the advent of AI and machine learning, the content which appeared innocuous can now be exploited and abused in the wrong hands. That means Facebook is forcing all apps that have previously been approved for accessing Events, Groups and Pages, have to be reviewed again.
For the developers working on these changes behind the scenes, it's a difficult process but something we monitor constantly to ensure the client experience is supported, and uncompromised. While at times frustrating, it’s also fascinating to watch the complexities of today's interconnected environment play, shift and unfold.
Ian Young, Isentia Technical Architect
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Blog
No warning to Facebook & Instagram changes
In the wake of the Facebook Cambridge Analytica scandal, there have been a myriad of changes impacting users of Facebook and Instagram content recently. These changes were made without any notice and were effective immediately which has impacted third-party apps worldwide.
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.
Service delivery agencies - these rely heavily on content freshness. They can’t risk outdated sources impacting eligibility or process changes not reaching audiences.
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
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.
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.
Ngaire Crawford, Pulsar Group’s Executive Director for AI Strategy says, “It’s easy to disregard LLM reputation as part of a difficult AI landscape or something that is only really relevant to more product-based communication or marketing. Government communications is about social licence, and ensuring the public have access to up to date and accurate information about things that matter to them, the role that Generative AI plays in how a community understand an issue will only continue to grow, and knowing the impact that you can have in that through small shifts in channel strategies or more consistent messaging is a crucial part of the communications toolkit.”
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.
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.