How to Interpret Hamilton 2.0

Version 2.0 of Hamilton 68 displays outputs from sources that we can directly attribute to the Russian government or its various news and information channels. These channels and accounts often engage with topics, hashtags, URLs, and people that are in no way affiliated with the Russian government. It would therefore be INCORRECT to, without further analysis, label anyone or anything that appears on the dashboard as being connected to Russian propaganda.

Note – The dashboard uses natural language processing and other machine learning and auto-translation tools to extract key information from the data. Although highly accurate, automated systems are imperfect. We urge all those reporting on the dashboard to confirm findings with ASD. 

How often is the dashboard updated?

The dashboard updates twice per day, meaning that Tweets, articles, and broadcasts from the current day may or may not be included on the dashboard (depending on the time of the content is posted or published). The default setting displays data from the previous 7 days, but users can filter data by any date range.

Twitter Data

What accounts are included?

The dashboard displays aggregate results from two categories of accounts: those of the Russian government and diplomatic corps and those connected to Russian state-funded media. Click here for the full account list.

What accounts are included in each category?

The Hamilton 2.0 dashboard monitors roughly 150 accounts representing individuals or entities connected to the Russian government or Russian state-funded media. The dashboard collects data on accounts that primarily target foreign audiences, namely those in Europe, the United States, the broader Anglosphere, and countries of key strategic interest to the Russian Federation (e.g., Syria, Venezuela, and Ukraine). We identified these accounts using basic open source research techniques. Most of them openly note their affiliation with the Russian government (i.e., these accounts represent overt rather than covert influencers). For research purposes, we aim to keep the account list consistent, but we audit the list on a monthly basis to add relevant accounts and to remove those that are defunct or no longer relevant.

We divided accounts into two broad categories: Russian diplomatic/government accounts and Russian state-funded media accounts. A detailed description of each category is below:

Russian diplomatic/government accounts

This category contains accounts of key individuals and institutions that represent the government of the Russian Federation, including:

  • All known embassy, consular, and ambassadorial accounts in Europe, the United States, Canada, New Zealand, Australia, South Africa, and countries of key geopolitical importance to the Russian Federation, including Ukraine, Venezuela, Syria, Iran and Israel.
  • Official accounts representing the Ministry of Foreign Affairs, as well as agencies and organizations that have an international or foreign policy focus (e.g., Russian Mission to NATO)
  • Key individuals within the Russian government

Note – In cases where there are two accounts representing one entity or person in different languages – e.g., @MedvedevRussia (Russian) and @MedvedevRussiaE (English) – only the English language account is included. Similarly, in cases where an embassy has a local language and a Russian language account, only the local language account is included (in order to avoid duplication). 

Russian state-funded media accounts

This category contains accounts representing Russia’s various state-funded media outlets, including:

  • Accounts connected to Russia’s state-funded international broadcasters and online news and information portals, including European-language versions of RT and Sputnik
  • Accounts connected to television programs on RT or “independent” outlets funded by Rossiya Segodnya (Russia Today)
  • Accounts of key management personnel

Note – The media account list does NOT include accounts connected to individual journalists, reporters, or television personalities associated with or in the employ of Russian state-funded media outlets. These accounts are often as influential, if not more influential, than official media accounts; however, we chose not to include these accounts for the following reasons:

  • Individual accounts may tweet personal opinions that do not reflect the official position(s) of the Russian Federation
  • ASD is opposed to any effort to target, harass, or dox individual journalists, regardless of their professional affiliation

Top 10 accounts

These charts display the most active, retweeted, and liked accounts during a specified time period. This information is useful in interpreting results on the rest of the dashboard. For example, the most active accounts will affect the top 10 results more than accounts that Tweet infrequently, regardless of the popularity of those accounts. Engagement metrics are determined using Twitter’s public API. Because the dashboard does not update in real-time, we urge users to check up-to-date engagement metrics on Twitter.com. 

Top 10 tweets

This chart displays the Tweets made by monitored accounts that have received the most engagement over a specified time period. Non-English Tweets are displayed in English using Microsoft’s Translator API. Engagement metrics are determined using Twitter’s public API. As noted above, we urge users to check up-to-date engagement metrics on Twitter.com.

Top 10 hashtags

This chart displays the hashtags (#) most frequently used by monitored accounts during a specified time period. Hashtags are useful indicators of topics of interest, but hashtags can be used either to support or undermine the specified cause or person. They therefore should be interpreted in the full context of the Tweet(s).

Top 10 mentions

This chart displays Twitter handles most frequently included in Tweets made by monitored accounts. These results include all mentions of (also known as tags), replies to, and retweets of a specific account. Accounts that are monitored on the dashboard (e.g., @RT_com) are filtered out, and therefore are NOT included.

WARNING: This data does not necessarily imply that the Russian government is supporting or targeting a mentioned user.

Top 10 key phrases

This chart displays the most-used phrases (including proper names, terms, etc.) that appear in Tweets made by monitored accounts during a specified time period. See below to learn how we extract key phrases from Tweets.

How are key phrases extracted from Tweets?

We use Microsoft’s Cognitive Services to translate non-English Tweets and to extract key phrases. Non-relevant or non-specific key phrases (e.g., verbs, common nouns, etc.) are filtered out to remove noise from the results. We extract key phrases instead of key words to link together related words (e.g., “INF Treaty” or “Barack Obama”). It is possible, however, for two or more related nouns to appear as multiple entries in search results. For example, “Trump,” “Donald Trump,” and “President Trump” may appear as three unique phrases. Searching for a term in the “key phrases” section of the FILTERS sidebar will reveal similar key phrases.   

Top 10 links

This chart displays the hyperlinks most shared by monitored accounts in a specified time period. It is important to note that the results display the specific URL provided in the Tweet(s), most of which have been shortened. Therefore, the top 10 results may not reflect the most shared URLs, as multiple shortened URLs may link to the same original URL. 

WARNING: The dashboard does not screen links for malware, phishing content, spam, or any other undesired content. Click on the links at your own risk.

Top 10 mentioned countries

Using key phrase extraction, this chart displays the countries most mentioned in Tweets during a specified time period. In addition, special territories and regions (e.g., Hong Kong and the EU) are included as individual entities in the country data.

NOTE: The chart lists all mentions of a country, including alternative country names, under that country’s official name (e.g., mentions of US, USA, U.S., and America are all included in tabulations for the United States of America).

Top 10 Tweets retweeted by monitored accounts

This chart displays the most popular Tweets (as determined by retweet metrics) that have been retweeted during a specified time period by at least one monitored account. The default setting displays retweets of accounts NOT monitored on the dashboard, including different language versions of accounts monitored on the dashboard (e.g., @MID_RF, the Russian language version of @MFA_Russia). The account that posted the original tweet is displayed in the chart; the monitored account(s) that retweeted that Tweet is/are displayed above in the Top 10 Accounts chart. The purpose of this chart is to display the messages and, occasionally, messengers being amplified by official Russian channels. 

WARNING: A retweet does not necessarily imply that the Russian government endorses the author or the content of a Tweet.

How are key phrases extracted from Tweets?

We use Microsoft’s Cognitive Services to translate non-English Tweets and to extract key phrases. Non-relevant or non-specific key phrases (e.g., verbs, common nouns, etc.) are filtered out to remove noise from the results. We extract key phrases instead of key words to link together related words (e.g., “INF Treaty” or “Barack Obama”). It is possible, however, for two or more related nouns to appear as multiple entries in search results. For example, “Trump,” “Donald Trump,” and “President Trump” may appear as three unique phrases. Searching for a term in the “key phrases” section of the FILTERS sidebar will reveal similar key phrases.

Broadcast Data

Daily summaries of RT’s broadcasts and YouTube content

The dashboard summarizes the outputs of RT’s daily news broadcast (12:00 and 17:00 MSK), and video content uploaded to RT America and RT UK’s YouTube channels (NOTE: YouTube videos over 20 minutes in length are NOT included). Each video segment represents a single YouTube clip or a standalone segment on RT’s broadcast news (NOTE: broadcast clips may contain two or more segments — identified by two distinct titles — though we attempt to manually remove extraneous information). Data is provided by our partners at VidRovr. To learn more about VidRovr click here

The titles associated with YouTube clips are those provided by the channels; the titles of broadcast segments are taken from the first chyron (or lower-third) that appears in each segment. The chyron information provides not only the topics discussed but also key contextual information, including segment titles, key quotes, editorialized context, and the names and titles of interviewees and those appearing on-screen. Human coders determine the countries and categories associated with clips. 

How does ASD collect this data?

Data is provided by Vidrovr, an enterprise video understanding platform. Vidrovr leverages proprietary machine learning and computer vision algorithms to determine who is speaking and appearing on screen, the key topics that are associated with a specific section, and what is appearing visually, among other things. For any inquiries concerning Vidrovr, please send an email to contact@vidrovr.com

Hamilton 68 uses VidRovr technology to extract text from the chyrons that appear in each segment. Although rare, the system occasionally does not recognize chyrons, particularly when they appear briefly on screen. Human reviewers edit chyrons for accuracy, but do not view each video and therefore will not necessarily catch missing or incomplete chyrons. To avoid repetition, we only include the first appearance of a chyron within a segment, although duplicate chyrons are included if the subtitle is different.

How often is the dashboard updated?

The dashboard updates twice per day, meaning that broadcasts from the current day may or may not be included on the dashboard (depending on the time of the content is posted or published). The default setting displays data from the previous 7 days, but users can filter data by any date range.

Due to the fact that human coders must categorize content, there occasionally will be one- or two-day lapses in manual coding, particularly during weekends and holiday periods. In addition, disruptions in video feeds will occasionally result in days when video data is not captured.  YouTube data will be backfilled as soon as possible; broadcast data, however, may not be able to be recaptured. 

How are associated countries identified?

Country information is determined by human coders. Coders base their determination on the textual data in the chyrons and titles, and only label countries that are of primary or secondary importance. Coders can tag multiple countries associated with an individual clip. In addition, special territories and regions (e.g., Hong Kong and the EU) are included as individual entities in the country data. 

How are key phrases extracted from videos?

We use Microsoft’s Cognitive Services to extract key phrases from chyrons and titles. Non-relevant or non-specific key phrases (e.g., verbs, common nouns, etc.) are filtered out to remove noise from the results. We extract key phrases instead of key words to link together related words (e.g., “INF Treaty” or “Barack Obama”). It is possible, however, for two or more related nouns to appear as multiple entries in search results. For example, “Trump,” “Donald Trump,” and “President Trump” may appear as three unique phrases. Searching for a term in the “key phrases” section of the FILTERS sidebar will reveal similar key phrases.

How are news categories coded?

Human coders categorize each segment based on the set of pre-determined categories and sub-categories listed below:

  • Business – Content related to specific business entities or a business sector not covered by one of the other categories
  • Celebrity/Gossip – Content related to celebrity news and gossip
  • Civil Disorder – Content related to protests, riots, strikes, etc.
  • Climate Change/Environment – Content related to climate change, including global warming, sea-level rise, climate science, etc.
  • Crime – Content related to violent crimes, missing persons, mass shootings, the criminal justice system, and other true crimes (not including police brutality – see Social Inequality)
  • Culture – Content related to music, film, television, theater, pop-culture events, festivals, etc.
  • Energy – Content related to the energy sector or energy politics/geopolitics
  • Free Speech/Censorship – Content related to censorship, press freedoms, and alleged bias in the technology sector
  • Geopolitics – Content related to foreign policy and international relations
  • Health/Safety – Content related to public safety issues, health advances, health concerns, global pandemics, health care systems, etc.
  • Human Interest – Content related to emotional coverage of a person, people, or pets
  • Income Inequality/Poverty – Content related to the wealth distribution, poverty, homelessness, minimum wage issues, etc.
  • International Economics/Trade – Content related to trade, the global economy, international sanctions, etc.  
  • Man-Made Disaster – Content related to plane/car crashes, explosions, fires, chemical spills, nuclear disasters and other human-induced calamitous events
  • Media Criticism – Content related to claims of media bias and criticism of the “mainstream,” Western, or specific media outlets
  • Migration/Immigration – Content related to migration or immigration issues
  • Military/War: Content related to war and conflicts between and among states, and content related to military exercises, training, military-technological developments, etc.
  • Natural Disaster – Content related to earthquakes, storms, floods, landslides, etc.
  • National Economy – Content related to domestic economies and financial sectors
  • Politics (U.S., U.K., Russia, Other) – Content related to domestic political affairs, elections, etc.
  • Political Scandals – Corruption, sex scandals, political investigations, electoral fraud/ballot stuffing, abuses of power, etc.  
  • Religion – Content related to religion or religious studies, but excluding religious discrimination (see social issues/inequality) 
  • Social Issues/Inequality – Content related to issues pertaining to racism, xenophobia, LGBTI rights, religious discrimination, social justice issues, etc.
  • Sports – Content related to team or individual sports, excluding gossip or scandals related to individual athletes (see Celebrity-Gossip)
  • Surveillance/Spying/Privacy – Content related to government or corporate abuses of privacy, including surveillance and spying
  • Technology – Content related to emerging technologies and the tech sector (not including military technology – see Military/War)
  • Terrorism – Content related to domestic or global terrorism, including incidents, threats, groups, etc.
  • Weather – Daily weather reports not related to natural disasters or climate change       

The purpose of categorical coding is to assist users in finding relevant material. All coders are trained in order to ensure consistency; however, due to the volume of content and the real-time nature of the dashboard, inter-coder tests are not always possible. Thus, the potential for human error and variability is greater than would be acceptable in an academic study. We therefore urge caution when using or citing categorical data. If you would like to help enhance our ability to code and verify this data, please donate to ASD at this link.

Website Data

The dashboard displays aggregate results from English-language websites and news portals funded by the Russian government. Currently, the dashboard collects data on RT.com, Sputniknews.com, RBTH.com (Russian Beyond the Headlines), and TASS.com (Russia News Agency). Data is provided by our partners at Debunk.EU, an initiative combating disinformation in Lithuania. Click here for more information about Debunk.EU.

Data sources

Data is extracted from article excerpts (first 200 words) from the four Russian state-funded websites monitored on the dashboard. This means that the metrics provided on the dashboard SHOULD NOT be considered a full and complete summation. It is also important to stress that key phrases and countries not mentioned at the beginning of articles will not be captured by the dashboard. Thus, the results should be interpreted as an approximation of key messaging interests, rather than as a complete tally of all terms and phrases in collected articles.

How often is the dashboard updated?

Website information is updated once per day, meaning that articles from the current day may or may not be included on the dashboard (depending on the time the content is posted or published). The default setting displays data from the previous 7 days, but users can filter data by any date range.

Top 10 articles by social media engagement

This chart displays the articles that have received the most engagement on Facebook and VKontakte (Russian social networking service) over a specified time period. Engagement numbers are from public pages only. Data is provided by Debunk.eu, and reflects accurate totals at the time the dashboard is updated each day, meaning that actual engagement numbers may vary depending on the time of day. 

Top 10 key phrases

This chart displays the most-used phrases (including proper names, terms, etc.) that appear in article excerpts and titles during a specified time period. See below to learn how we extract key phrases from articles.

How are key phrases extracted from articles?

We use Microsoft’s Cognitive Services to extract key phrases from article excerpts and titles. Non-relevant or non-specific key phrases (e.g., verbs, common nouns, etc.) are filtered out to remove noise from the results. We extract key phrases instead of key words to link together related words (e.g., “INF Treaty” or “Barack Obama”). It is possible, however, for two or more related nouns to appear as multiple entries in search results. For example, “Trump,” “Donald Trump,” and “President Trump” may appear as three unique phrases. Searching for a term in the “key phrases” section of the FILTERS sidebar will reveal similar key phrases.

Top 10 countries

Using key phrase extraction (see above to learn how we extract key phrases), this chart displays the countries most mentioned in article excerpts during a specified time period. In addition, special territories and regions (e.g., Hong Kong and the EU) are included as individual entities in the country data.

NOTE: The chart lists all mentions of a country, including alternative country names, under that country’s official name (e.g., mentions of US, USA, U.S., and America are all included in tabulations for the United States of America).