Doug Bania

“My specialty is using Internet and social media analysis when I'm quantifying value or I'm calculating damages, or if I'm analyzing the impact of social media or Internet events.”

Establishes the core expertise that qualifies Bania to opine on Depp's reputational harm through digital metrics.

“I reviewed the top three because research shows that about 50 to 75 percent of the people only click on the top three. So I wanted to get the majority of the searches.”

Provides the methodological rationale for limiting analysis to top three search results, preempting challenge to sample scope.

“Yeah, Mr. Depp was portrayed in a negative connotation after the 2016 allegations of abuse, and even more so after the 2018.”

Concise summary of the directional finding tying the negative public image shift to Heard's allegations and the op-ed.

“the public perception of Mr. Depp has been damaged. You know, they like him less and they dislike him more.”

Plain-language bottom-line conclusion from the Q score data, framed for jury comprehension.

“Well, that is correct because Google Trends is based on a search of a word or a name. And because Mr. Depp's name was not mentioned in that op-ed, Google Trends did not pick that up.”

Bania concedes the core structural limitation of his Google Trends analysis: the op-ed never registered in searches for Johnny Depp because his name was absent from the text.

“Well, you're talking about statistically a difference. What I'm talking about is how we use Q scores in the industry. When you see a Q score that's dropping from a 31 to a 29, there's an issue. Is this somebody you really want to hire to endorse your products or service? No, probably not. You want to look into why. Why? What is going on in the public to make these Q scores drop like that?”

Bania defends an industry-practical interpretation of Q score changes against Nadelhaft's statistical-significance challenge, after his deposition had conceded he was not offering an opinion on significance.

“As I mentioned, my analysis looked at the snapshot of time and it shows that he was harmed, you know, from before the allegations of abuse in to after the op-ed in 2018.”

Bania maintains his 'snapshot' methodology after the fuller dataset undermined his three-point Q score selection, acknowledging the limited scope while defending its conclusion.

“Q scores can go up and down. You want to analyze the time and see what's going on out in the media.”

Bania grounds his monitoring methodology in standard industry practice, establishing context for his analytical choices.

“he's portrayed in a negative connotation after that date.”

Bania's core opinion on the op-ed's effect on Depp's public image, directly rehabilitating the cross-examination suggestion he was not offering such an opinion.

“We want to see what's happening right before an event, during that event, and if there's another event, after that event.”

Bania's rationale for why three Q score data points are the appropriate methodology, responding to the cross-examination challenge about examining only a subset of available data.

“Mr. Schnell provided no evidence of a correlation between the Waldman statements and the hashtags and the spikes of those hashtags on Twitter.”

Bania's opening salvo against Schnell's methodology, framing the entire rebuttal around the absence of any proven link between the Waldman statements and social media activity.

“only 2 percent of all of the tweets happened during this Waldman statement period”

The core quantitative finding undermining Schnell's analysis: the vast majority of hashtag activity occurred outside the period when the Waldman statements could have caused it.

“I identified five tweets that were related to the Waldman statements.”

Bania reduces Schnell's 2.7 million tweets to just five actually referencing the Waldman statements, effectively dismantling the evidentiary basis for Heard's social media damages claim.

“She didn't even know what causation was.”

Bania's sharpest criticism of Arnold, arguing she lacked the methodological foundation to calculate damages without first establishing causation.

“I am a damages expert, but not providing any quantitative damages opinions in this case.”

Bania draws a distinction between his general expertise and his limited role in this proceeding, setting the scope of his rebuttal testimony.

“Yeah, so I used them in quotes because, you know, hoax could be used in many other contexts, so I wanted to make sure I was fitting my search with the theme of the Waldman statements.”

Bania explains his rationale for exact-phrase matching, which Nadelhaft uses to demonstrate the methodology's narrow capture rate.

“The July spike, which is number 2, is not related to the Waldman statements, and there are articles related to abuse between Heard and Depp and feces found in Depp's bed.”

Bania attributes a major post-Waldman hashtag spike to unrelated coverage, illustrating his consistent effort to disconnect spikes from the defamatory statements.

“First of all, I don't agree that "justice for Johnny Depp" is a negative hashtag toward Amber Heard.”

Bania disputes a foundational premise of Schnell's dataset — the characterization of pro-Depp hashtags as anti-Heard — revealing a definitional disagreement underlying the competing analyses.