List of keywords used to build the text classifier for the paper Reviewing War: Unconventional User Reviews as a Side Channel to Circumvent Information Controls. For more information on how these keywords were obtained, see the "Data Labeling" section of this paper. The provided CSV file contains 3 columns: "keyword": Lowercased keyword in either English, Russian, Ukranian or Polish. "weight": Score indicating the keyword's war-related affinity, with 3 being the most related. Negative weights are used to correct for exceptions in our classifier. "topic": Subject of the keyword used for topic analysis.

List of keywords used to build the text classifier for the paper Reviewing War: Unconventional User Reviews as a Side Channel to Circumvent Information Controls. For more information on how these keywords were obtained, see the "Data Labeling" section of this paper. The provided CSV file contains 3 columns: "keyword": Lowercased keyword in either English, Russian, Ukranian or Polish. "weight": Score indicating the keyword's war-related affinity, with 3 being the most related. Negative weights are used to correct for exceptions in our classifier. "topic": Subject of the keyword used for topic analysis.

In this paper, we report on a measurement study by researchers from several institutions that collected and analyzed network data to assess the impact of the first wave of COVID-19 (February-June 2020) on the Internet traffic. The datasets from Internet Service Providers, Internet Exchange Points, and academic networks, primarily in Europe, provide a unique view on the changes of Internet traffic due to pandemic and the lockdown that forced hundreds of millions of citizens to stay and work from home. The analysis shows that the increase of Internet traffic was about 15-20 % within a couple of weeks, an increase that is typically spread over multiple months under typical operation. However, traffic during peak hours does not increase by more than 5 %. The increase was noticeably higher for specific applications, e.g., remote work applications, teleconferencing, video on demand; in some cases up to 200 %. However, overall, the Internet reacted well to these unprecedented times.

The impact of Internet phenomena depends on how they impact users, but researchers lack visibility into how to translate Internet events into their impact. Distressingly, the research community seems to have lost hope of obtaining this information without relying on privileged viewpoints. We argue for optimism thanks to new network measurement methods and changes in Internet structure which make it possible to construct an "Internet traffic map". This map would identify the locations of users and major services, the paths between them, and the relative activity levels routed along these paths. We sketch our vision for the map, detail new measurement ideas for map construction, and identify key challenges that the research community should tackle. The realization of an Internet traffic map will be an Internet-scale research effort with Internet-scale impacts that reach far beyond the research community, and so we hope our fellow researchers are excited to join us in addressing this challenge.