Learning from climate change news: Is the world on the same page?

roughly be explained as the model being 4 editions off, although the metric is in fact more complex. Considering that there are 26 COP meetings, not every edition is as impactful and most characteristics change gradually rather than at once, these scores shall be considered acceptable. The most informative features of regression models are only based on a single set of positive and negative coefficients. Since n-grams are represented by positive tf-idf importance scores, these respectively refer to an increase or a decrease of the predicted COP meeting number. Looking at the top of the positive and negative features, conclusions can therefore only be drawn in terms of phrases for later and earlier COP meetings. This seems to reflect many of the findings done with the classification model. Several examples are given below, for earlier (negative features, in red ) and later COPs (positive features, in greenþ). • Terminology The terminology found using classification comes back in the regression model. Terminol- ogy has shifted to become more descriptive of a trend (greenhouse vs. climate) and more extreme (climate crisis). It also seems that carbon dioxide is now more frequently referred to merely as carbon. Earlier: greenhouse, global warming, greenhouse emissions, carbon dioxide, environmentalists, earth, climatic, environment, greenhouse effect, carbon dioxide emissions Later: climate, planet, carbon, climate crisis, emissions, CO2, footprint, climate emergency, carbon emissions • Causes

Similarly, phrases that describe the causes of climate change largely matched those found before. It does seem that describing causes is something of the later editions. However, this is in fact sound with the findings that intermediate meetings like COP20 until 23 are character- ized more in terms of causes. Earlier: petroleum, gas, traffic Later: aircraft, shale, fracking, diesel, air pollution, plastic, coal, methane, drilling, vehicles, shale oil, oilsands • Effects Some effects were found in the most informative features, though much less than for the classification model. An interesting word that is yielded, is ozone, referring to the ozone layer hole. This was more of a concern earlier but seems to be on its return under the effect of the Montreal Protocol (unep.org/ozonaction/who-we-are/about-montreal-protocol). It is shown that the media wrote a lot more about it during earlier COP meetings. Earlier: ozone, smog, air conditioning Later: bushfires • Measures The potential trend that measures are becoming more and more subject of attention seems to be reflected by the yields of the regression model. No features that describe measures were found on the negative side of the coefficient spectrum, whereas quite some could be detected with positive scores. These phrases are predominantly the same as for classification. Though sustainability and electric vehicles are interesting additions. Later: electric, electric vehicles, battery, and solar, renewables, sustainability, emissions reduction PLOS ONE Learning from climate change news

PLOS ONE | https://doi.org/10.1371/journal.pone.0297644 March 20, 2024 21 / 27