3 ms·

> I prove a history of disproportionate bias against Palestinians in the New York Times. This is a really bold statement for any analysis and seems odd to come

> I prove a history of disproportionate bias against Palestinians in the New York Times. This is a really bold statement for any analysis and seems odd to come put of academic work that’s supervised. This preprint is submitted to the Journal of Palestinian Studies so it will be interesting to see how their peer review checks this out. I don’t quite understand this conclusion based on the paper as it seems like the author looked for existence of some words and for use of active vs passive voice. I don’t understand how active vs passive voice is a sign of bias unless you control for many other factors not mentioned. Are specific authors more likely, is time period affected, are other topics similar, etc etc. I don’t get the logic that this shows a bias in general and don’t see anything presented about why these 33k articles are different. Similarly, I’m not sure how tracking the mention of Palestinian or Israeli people just by word count means anything. Wouldn’t this be impacted by events, this isn’t addressed in the paper. Are there more deaths or attacks in different groups. This seems important to address, but I couldn’t find anything. I’m also not sure how the 33k articles were selected so whether articles were included or excluded would impact these results. Similarly not sure if the sentiment analysis of the NLP kits she used is similar or dissimilar from NYT in general. And the determination of violent language seems like a manual exercise with no validation and would like to know more about the methods used to create the set of violent words. I don’t see the actual training_data.csv that the author created and would be interested to see what was actually made since that file seems to be the output of a manual process to sample 500 articles and pick words.

md_ 5y ago
These are good points. I think the claims are a bit bold. I do think the "active vs passive voice" is an interesting metric, since it seems intuitively a bit harder to know why that would differ for the two groups. As I noted below, in the US it's common to note that the phrase "officer-involved shooting" (i.e., passive voice) is often used to describe cases where police officers shoot someone, but "dog-involved biting" is rarely used to describe the case where a dog bites someone. This strikes me as a convincing (though perhaps not ironclad) argument for how such metrics—which are seemingly independent of the rate of mentions (which itself could be reflecting world events)—can shed light on authorial bias. I think you could construct similar "event-independent" metrics; for example, are victims of violence more or less likely to be named when they are of one group or another? Are direct quotes from spokespeople more likely to be used from one group or another? Etc. I generally argue against trying to make all journalism just "impartial he-said, she-said", so I'm a little uncomfortable with this exercise, but, again, the "officer-involved shooting" case is one where very clear language bias seems to affect the discourse.
- prepend 5y ago
  I think the active/passive thing is worth expiration. But to 1) conclude that passive=bad seems to need evidence for why that is and 2) is there a significant difference for the Israeli/Palestine article set. Both of those seem just stated without evidence so it seems odd that the MIT supervisors would have a student write this us.
gher-shyu3i 5y ago
> This is a really bold statement It's obvious. Any entity or agency that sides with the Zionist state, which was formed on stolen and occupied Palestinian lands, is biased. The tides finally seem to be changing, and truth is starting to dawn on people.

md_ 5y ago

These are good points. I think the claims are a bit bold. I do think the "active vs passive voice" is an interesting metric, since it seems intuitively a bit harder to know why that would differ for the two groups. As I noted below, in the US it's common to note that the phrase "officer-involved shooting" (i.e., passive voice) is often used to describe cases where police officers shoot someone, but "dog-involved biting" is rarely used to describe the case where a dog bites someone. This strikes me as a convincing (though perhaps not ironclad) argument for how such metrics—which are seemingly independent of the rate of mentions (which itself could be reflecting world events)—can shed light on authorial bias. I think you could construct similar "event-independent" metrics; for example, are victims of violence more or less likely to be named when they are of one group or another? Are direct quotes from spokespeople more likely to be used from one group or another? Etc. I generally argue against trying to make all journalism just "impartial he-said, she-said", so I'm a little uncomfortable with this exercise, but, again, the "officer-involved shooting" case is one where very clear language bias seems to affect the discourse.

prepend 5y ago
I think the active/passive thing is worth expiration. But to 1) conclude that passive=bad seems to need evidence for why that is and 2) is there a significant difference for the Israeli/Palestine article set. Both of those seem just stated without evidence so it seems odd that the MIT supervisors would have a student write this us.

gher-shyu3i 5y ago

> This is a really bold statement It's obvious. Any entity or agency that sides with the Zionist state, which was formed on stolen and occupied Palestinian lands, is biased. The tides finally seem to be changing, and truth is starting to dawn on people.