Media Manipulation and Bias Detection
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Critics of the deportation campaign (Democrats, civil-liberties–oriented critics, business leaders, local officials)
Caution! Due to inherent human biases, it may seem that reports on articles aligning with our views are crafted by opponents. Conversely, reports about articles that contradict our beliefs might seem to be authored by allies. However, such perceptions are likely to be incorrect. These impressions can be caused by the fact that in both scenarios, articles are subjected to critical evaluation. This report is the product of an AI model that is significantly less biased than human analyses and has been explicitly instructed to strictly maintain 100% neutrality.
Nevertheless, HonestyMeter is in the experimental stage and is continuously improving through user feedback. If the report seems inaccurate, we encourage you to submit feedback , helping us enhance the accuracy and reliability of HonestyMeter and contributing to media transparency.
Information is presented in a way that subtly influences interpretation, for example by consistently using one framing (e.g., 'killing' by agents) without parallel framing of the same events from other key perspectives.
The article repeatedly uses formulations such as: - "following widespread outcry over the killing of two US citizens by federal agents." - "the Jan. 24 fatal shooting of 37-year-old intensive care nurse Alex Pretti by a Border Patrol agent during an enforcement operation." - "Pretti’s death came just weeks after the Jan. 7 killing of Renee Good, a US citizen and Minneapolis mother of three, by an ICE agent during a similar operation in a residential neighborhood of the city." These descriptions are factually accurate as far as the text indicates, but they emphasize the victims’ sympathetic characteristics ("intensive care nurse", "mother of three") and the fact that they are US citizens, while not providing any detail about the agents’ stated accounts, internal reports, or legal findings. This can subtly frame the events primarily as unjustified killings by federal agents, even though the article later notes that Trump declined to say whether the shooting was justified and that an investigation is ongoing.
Add the law-enforcement perspective where available, clearly attributed, for parallel framing. For example: "...following widespread outcry over the killing of two US citizens by federal agents, incidents that officials say occurred during enforcement operations and are under investigation."
When describing the victims, balance humanizing details with neutral description of the circumstances and any relevant official accounts. For example: "...the Jan. 24 fatal shooting of 37-year-old Alex Pretti, an intensive care nurse, during a Border Patrol enforcement operation. Authorities say [brief summary of agents’ stated account], while critics argue [brief summary]."
Explicitly note when certain perspectives are not yet available: "Law-enforcement agencies have not publicly released a detailed account of the agents’ actions in the shootings." This clarifies that the imbalance is due to information availability, not editorial choice.
Leaving out relevant context or perspectives that would help readers fully understand an event, which can create a subtle imbalance even if the included information is accurate.
On the shootings, the article provides: - Victims’ identities and sympathetic details ("intensive care nurse", "mother of three"). - The fact that they were US citizens. - That they were killed by federal agents during enforcement operations. - That initial statements by Noem and Miller were criticized and that video "didn’t show Pretti brandishing the firearm" and "suggested that the officers had disarmed him before shooting him repeatedly." However, it does not provide: - Any direct statement from the Border Patrol, ICE, or the specific agents involved about their version of events. - Any mention of whether the agents are under internal investigation, placed on leave, or any preliminary findings from law-enforcement or independent investigators. This omission makes the law-enforcement side of the specific incidents underrepresented compared with the political and public-opinion angles, even though the broader administration perspective is covered.
Include any available official statements from Border Patrol, ICE, or the agents’ representatives, clearly attributed. For example: "ICE said in a statement that the agent fired after [their account], and that the incident is under internal review."
If such statements are not available, explicitly state that: "Border Patrol and ICE have not publicly released detailed accounts from the agents involved." This signals to readers that the omission is due to lack of public information, not selective reporting.
Briefly note the procedural status (e.g., "The agents involved have been placed on administrative leave pending investigation"), if known, to give a fuller picture of institutional response.
Early information in a story can disproportionately shape readers’ interpretation of later details, especially when emotionally salient facts are front-loaded.
The lead sentence anchors the reader on: "widespread outcry over the killing of two US citizens by federal agents." This is followed by detailed identification of the victims and the political fallout. Only later does the article mention that Trump declined to say whether the shooting was justified and that a "big investigation" is underway. Because the first impression emphasizes "killing" and "widespread outcry" without early mention that the incidents are under investigation and that law-enforcement accounts are not fully presented, readers may form an early, more one-sided view of the events.
In the lead or second sentence, add a brief clause indicating that the incidents are under investigation. For example: "...over the killing of two US citizens by federal agents, incidents that are now the subject of federal and local investigations."
Move or echo the mention of the ongoing investigation closer to the top of the article so that readers encounter it before or alongside the most emotionally charged descriptions.
Where possible, summarize in one early sentence that there are conflicting views about the incidents (e.g., "The shootings have prompted investigations and sharply differing accounts from officials and critics.") to signal complexity from the outset.
Using emotionally charged details that, while true, are selected in a way that can steer readers’ feelings more than their understanding.
The article highlights that the victims were: - "37-year-old intensive care nurse Alex Pretti" - "Renee Good, a US citizen and Minneapolis mother of three" These details are relevant and common in news reporting, but they are exclusively humanizing and sympathetic, with no parallel humanizing or contextual detail about the agents (e.g., training, years of service, or the risks they face). Combined with the lack of the agents’ own accounts, this can subtly tilt emotional response against the law-enforcement side of the incidents, even though the broader policy and political coverage is balanced.
Maintain the humanizing details about victims (they are newsworthy) but add neutral, factual context about the agents’ roles and the operational environment, if available (e.g., "The Border Patrol agent, assigned to a fugitive operations team, was conducting an early-morning arrest operation in a residential neighborhood.").
Clarify that the article is not making a judgment about justification, for example by adding: "Authorities have not yet released a full account of the agents’ actions, and no official determination has been made about whether the shootings were justified."
Ensure that emotionally salient details are balanced with procedural and factual information (investigations, legal standards, etc.) so that readers can form views based on process and evidence, not only sympathy.
- This is an EXPERIMENTAL DEMO version that is not intended to be used for any other purpose than to showcase the technology's potential. We are in the process of developing more sophisticated algorithms to significantly enhance the reliability and consistency of evaluations. Nevertheless, even in its current state, HonestyMeter frequently offers valuable insights that are challenging for humans to detect.