Listen offers a number of Ready to Use generational Social Panels for X (Twitter) and Reddit. Visit our article on using Social Panels in Listen to learn more.
This article will provide detailed information on what's included in our current Social Panel offerings for Listen.
In this article:
English language panels
| Panel name | Number of authors | Creation method | Methodology |
|---|---|---|---|
| Vegans (EN) | 184k | Author search | This panel contains authors that describe themselves with terms related to veganism. We searched relevant terms in authors’ bios to see if they are vegan. We used a total of 17 search terms. These include:
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| Gender - Women (EN) | 5m | Author search | This panel contains authors that describe themselves with terms related to being a woman. We searched relevant terms in authors’ bios to see if they are a woman. We used a total of 21 search terms. These include:
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| Gender - They/Them (EN) | 220k | Author search | This panel contains authors that describe themselves with terms related to they/them. We searched relevant terms in authors’ bios to see if they define themselves as they/them. We used a total of 5 search terms. These include:
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| Gender - She/Her (EN) | 1m | Author search | This panel contains authors that describe themselves with terms related to she/her. We searched relevant terms in authors’ bios to see if they define themselves as she/her. We used a total of 6 search terms. These include:
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| Gender - Men (EN) | 4m | Author search | This panel contains authors that describe themselves with terms related to being a man. We searched relevant terms in authors’ bios to see if they are a man. We used a total of 20 search terms. These include:
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| Gender - He/Him (EN) | 527k | Author search | This panel contains authors that describe themselves with terms related to he/him. We searched relevant terms in authors’ bios to see if they define themselves as he/him. We used a total of 6 search terms. These include:
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| Right Wing Politicians (EN) | 2,074 | Author search | This panel contains authors that describe themselves with terms related to right wing politicians. We searched relevant terms in authors’ bios to see if they are a right wing politician. We used a total of 148 search terms. These include:
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| Left Wing Politicians (EN) | 1,000 | Author search | This panel contains authors that describe themselves with terms related to left wing politicians. We searched relevant terms in authors’ bios to see if they are a left wing politician. We used a total of 195 search terms. These include:
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| Execs/Business leaders (EN) | 3m | Author search | This panel contains authors that describe themselves with terms related to being an executive or business leader. We searched relevant terms in authors’ bios to see if they are an executive or business leader. We used a total of 195 search terms. These include:
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English language generational social panels
| Panel name | Number of authors | Creation method | Methodology |
|---|---|---|---|
| Baby Boomers (EN) | 735k | Author search + Mentions search |
This panel contains X (Twitter) authors that describe themselves with terms related to baby boomers in English. We searched relevant age-related terms in authors’ bios and posts (tweets) to infer if they are a baby boomer (birth years 1947 through 1965). For posts (tweets), authors were collected and assigned ages based on direct, precise mentions of age within the last ten years of X (Twitter) data. For author bios, authors' most recent bio descriptions were searched to find direct, precise mentions of age and any indicated age assigned to the author. These mentions and bios were then collated per author, and any authors whose statements indicated conflicting ages were removed from the panel. To improve the panel's focus on consumer personas, prominent authors (500k+ followers) were excluded from the panel. Here are a few example search terms that we used for this panel:
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| Gen X (EN) | 878K | Author search + Mentions search |
This panel contains X (Twitter) authors that describe themselves with terms related to generation X in English. We searched relevant age-related terms in authors’ bios and posts (tweets) to infer if they are part of generation X (birth years 1966 through 1980). For posts (tweets), authors were collected and assigned ages based on direct, precise mentions of age within the last ten years of X (Twitter) data. For author bios, authors' most recent bio descriptions were searched to find direct, precise mentions of age and any indicated age assigned to the author. These mentions and bios were then collated per author, and any authors whose statements indicated conflicting ages were removed from the panel. To improve the panel's focus on consumer personas, prominent authors (500k+ followers) were excluded from the panel. Here are a few example search terms that we used for this panel:
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| Gen Y / Millennials (EN) | 3.2M | Author search + Mentions search |
This panel contains X (Twitter) authors that describe themselves with terms related to millennials in English. We searched relevant age-related terms in authors’ bios and posts (tweets) to infer if they are a millennial (birth years 1981 through 1995). For posts (tweets), authors were collected and assigned ages based on direct, precise mentions of age within the last ten years of X (Twitter) data. For author bios, authors' most recent bio descriptions were searched to find direct, precise mentions of age and any indicated age assigned to the author. These mentions and bios were then collated per author, and any authors whose statements indicated conflicting ages were removed from the panel. To improve the panel's focus on consumer personas, prominent authors (500k+ followers) were excluded from the panel. Here are a few example search terms that we used for this panel:
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| Gen Z (EN) | 2.4M | Author search + Mentions search |
This panel contains X (Twitter) authors that describe themselves with terms related to generation Z in English. We searched relevant age-related terms in authors’ bios and posts (tweets) to infer if they are part of generation Z (birth years 1996 through 2012). For posts (tweets), authors were collected and assigned ages based on direct, precise mentions of age within the last ten years of X (Twitter) data. For author bios, authors' most recent bio descriptions were searched to find direct, precise mentions of age and any indicated age assigned to the author. These mentions and bios were then collated per author, and any authors whose statements indicated conflicting ages were removed from the panel. To improve the panel's focus on consumer personas, prominent authors (500k+ followers) were excluded from the panel. No terms related to ages below 18 were included in our search, and any author inferred to be under 18 at time of posting is excluded from this panel. Here are a few example search terms that we used for this panel:
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French language generational social panels
| Panel name | Number of authors | Creation method | Methodology |
|---|---|---|---|
| Baby Boomers (FR) | 23K | Author search + Mentions search |
This panel contains X (Twitter) authors that describe themselves with terms related to baby boomers in French. We searched relevant age-related terms in authors’ bios and posts (tweets) to infer if they are a baby boomer (birth years 1947 through 1965). For posts (tweets), authors were collected and assigned ages based on direct, precise mentions of age within the last ten years of X (Twitter) data. For author bios, authors' most recent bio descriptions were searched to find direct, precise mentions of age and any indicated age assigned to the author. These mentions and bios were then collated per author, and any authors whose statements indicated conflicting ages were removed from the panel. To improve the panel's focus on consumer personas, prominent authors (500k+ followers) were excluded from the panel. Here are a few example search terms that we used for this panel:
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| Gen X (FR) | 38K | Author search + Mentions search |
This panel contains X (Twitter) authors that describe themselves with terms related to generation X in French. We searched relevant age-related terms in authors’ bios and posts (tweets) to infer if they are part of generation X (birth years 1966 through 1980). For posts (tweets), authors were collected and assigned ages based on direct, precise mentions of age within the last ten years of X (Twitter) data. For author bios, authors' most recent bio descriptions were searched to find direct, precise mentions of age and any indicated age assigned to the author. These mentions and bios were then collated per author, and any authors whose statements indicated conflicting ages were removed from the panel. To improve the panel's focus on consumer personas, prominent authors (500k+ followers) were excluded from the panel. Here are a few example search terms that we used for this panel:
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| Gen Y / Millennials (FR) | 128K | Author search + Mentions search |
This panel contains X (Twitter) authors that describe themselves with terms related to millennials in French. We searched relevant age-related terms in authors’ bios and posts (tweets) to infer if they are a millennial (birth years 1981 through 1995). For posts (tweets), authors were collected and assigned ages based on direct, precise mentions of age within the last ten years of X (Twitter) data. For author bios, authors' most recent bio descriptions were searched to find direct, precise mentions of age and any indicated age assigned to the author. These mentions and bios were then collated per author, and any authors whose statements indicated conflicting ages were removed from the panel. To improve the panel's focus on consumer personas, prominent authors (500k+ followers) were excluded from the panel. Here are a few example search terms that we used for this panel:
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| Gen Z (FR) | 202K | Author search + Mentions search |
This panel contains X (Twitter) authors that describe themselves with terms related to generation Z in French. We searched relevant age-related terms in authors’ bios and posts (tweets) to infer if they are part of generation Z (birth years 1996 through 2012). For posts (tweets), authors were collected and assigned ages based on direct, precise mentions of age within the last ten years of X (Twitter) data. For author bios, authors' most recent bio descriptions were searched to find direct, precise mentions of age and any indicated age assigned to the author. These mentions and bios were then collated per author, and any authors whose statements indicated conflicting ages were removed from the panel. To improve the panel's focus on consumer personas, prominent authors (500k+ followers) were excluded from the panel. No terms related to ages below 18 were included in our search, and any author inferred to be under 18 at time of posting is excluded from this panel.
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Spanish language generational social panels
| Panel name | Number of authors | Creation method | Methodology |
|---|---|---|---|
| Baby Boomers (ES) | 105K | Author search + Mentions search |
This panel contains X (Twitter) authors that describe themselves with terms related to baby boomers in Spanish. We searched relevant age-related terms in authors’ bios and posts (tweets) to infer if they are a baby boomer (birth years 1947 through 1965). For posts (tweets), authors were collected and assigned ages based on direct, precise mentions of age within the last ten years of X (Twitter) data. For author bios, authors' most recent bio descriptions were searched to find direct, precise mentions of age and any indicated age assigned to the author. These mentions and bios were then collated per author, and any authors whose statements indicated conflicting ages were removed from the panel. To improve the panel's focus on consumer personas, prominent authors (500k+ followers) were excluded from the panel. Here are a few example search terms that we used for this panel:
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| Gen X (ES) | 142K | Author search + Mentions search |
This panel contains X (Twitter) authors that describe themselves with terms related to generation X in Spanish. We searched relevant age-related terms in authors’ bios and posts (tweets) to infer if they are part of generation X (birth years 1966 through 1980). For posts (tweets), authors were collected and assigned ages based on direct, precise mentions of age within the last ten years of X (Twitter) data. For author bios, authors' most recent bio descriptions were searched to find direct, precise mentions of age and any indicated age assigned to the author. These mentions and bios were then collated per author, and any authors whose statements indicated conflicting ages were removed from the panel. To improve the panel's focus on consumer personas, prominent authors (500k+ followers) were excluded from the panel. Here are a few example search terms that we used for this panel:
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| Gen Y / Millennials (ES) | 387K | Author search + Mentions search |
This panel contains X (Twitter) authors that describe themselves with terms related to millennials in Spanish. We searched relevant age-related terms in authors’ bios and posts (tweets) to infer if they are a millennial (birth years 1981 through 1995). For posts (tweets), authors were collected and assigned ages based on direct, precise mentions of age within the last ten years of X (Twitter) data. For author bios, authors' most recent bio descriptions were searched to find direct, precise mentions of age and any indicated age assigned to the author. These mentions and bios were then collated per author, and any authors whose statements indicated conflicting ages were removed from the panel. To improve the panel's focus on consumer personas, prominent authors (500k+ followers) were excluded from the panel. Here are a few example search terms that we used for this panel:
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| Gen Z (ES) | 474K | Author search + Mentions search |
This panel contains X (Twitter) authors that describe themselves with terms related to generation Z in Spanish. We searched relevant age-related terms in authors’ bios and posts (tweets) to infer if they are part of generation Z (birth years 1996 through 2012). For posts (tweets), authors were collected and assigned ages based on direct, precise mentions of age within the last ten years of X (Twitter) data. For author bios, authors' most recent bio descriptions were searched to find direct, precise mentions of age and any indicated age assigned to the author. These mentions and bios were then collated per author, and any authors whose statements indicated conflicting ages were removed from the panel. To improve the panel's focus on consumer personas, prominent authors (500k+ followers) were excluded from the panel. No terms related to ages below 18 were included in our search, and any author inferred to be under 18 at time of posting is excluded from this panel.
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German language generational social panels
| Panel name | Number of authors | Creation method | Methodology |
|---|---|---|---|
| Baby Boomers (DE) | 11K | Author Search + Mentions Search |
This panel contains X (Twitter) authors that describe themselves with terms related to baby boomers in German. We searched relevant age-related terms in authors’ bios and posts (tweets) to infer if they are a baby boomer (birth years 1947 through 1965). For posts (tweets), authors were collected and assigned ages based on direct, precise mentions of age within the last ten years of X (Twitter) data. For author bios, authors' most recent bio descriptions were searched to find direct, precise mentions of age and any indicated age assigned to the author. These mentions and bios were then collated per author, and any authors whose statements indicated conflicting ages were removed from the panel. To improve the panel's focus on consumer personas, prominent authors (500k+ followers) were excluded from the panel. Here are a few example search terms that we used for this panel:
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| Gen X (DE) | 18K | Author Search + Mentions Search |
This panel contains X (Twitter) authors that describe themselves with terms related to generation X in German. We searched relevant age-related terms in authors’ bios and posts (tweets) to infer if they are part of generation X (birth years 1966 through 1980). For posts (tweets), authors were collected and assigned ages based on direct, precise mentions of age within the last ten years of X (Twitter) data. For author bios, authors' most recent bio descriptions were searched to find direct, precise mentions of age and any indicated age assigned to the author. These mentions and bios were then collated per author, and any authors whose statements indicated conflicting ages were removed from the panel. To improve the panel's focus on consumer personas, prominent authors (500k+ followers) were excluded from the panel. Here are a few example search terms that we used for this panel:
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| Gen Y / Millennials (DE) | 34K | Author Search + Mentions Search |
This panel contains X (Twitter) authors that describe themselves with terms related to millennials in German. We searched relevant age-related terms in authors’ bios and posts (tweets) to infer if they are a millennial (birth years 1981 through 1995). For posts (tweets), authors were collected and assigned ages based on direct, precise mentions of age within the last ten years of X (Twitter) data. For author bios, authors' most recent bio descriptions were searched to find direct, precise mentions of age and any indicated age assigned to the author. These mentions and bios were then collated per author, and any authors whose statements indicated conflicting ages were removed from the panel. To improve the panel's focus on consumer personas, prominent authors (500k+ followers) were excluded from the panel. Here are a few example search terms that we used for this panel:
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| Gen Z (DE) | 31K | Author Search + Mentions Search |
This panel contains X (Twitter) authors that describe themselves with terms related to generation Z in German. We searched relevant age-related terms in authors’ bios and posts (tweets) to infer if they are part of generation Z (birth years 1996 through 2012). For posts (tweets), authors were collected and assigned ages based on direct, precise mentions of age within the last ten years of X (Twitter) data. For author bios, authors' most recent bio descriptions were searched to find direct, precise mentions of age and any indicated age assigned to the author. These mentions and bios were then collated per author, and any authors whose statements indicated conflicting ages were removed from the panel. To improve the panel's focus on consumer personas, prominent authors (500k+ followers) were excluded from the panel. No terms related to ages below 18 were included in our search, and any author inferred to be under 18 at time of posting is excluded from this panel.
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Reddit generational social panels
| Panel name | Number of authors | Creation method | Methodology |
|---|---|---|---|
| Reddit Panel - Baby Boomers (EN, DE, ES, FR) | 95k | Mentions Search | This panel contains Reddit authors that describe themselves with terms related to baby boomers in English, German, Spanish and French. We searched relevant age-related terms in authors’ posts and comments to infer if they are a baby boomer. This panel contains Reddit authors that describe themselves with terms related to baby boomers in English, German, Spanish and French. We searched relevant age-related terms in authors’ posts and comments to infer if they are a baby boomer. Authors were collected and assigned ages based on direct, precise mentions of age in their posts or comments within the last ten years of Reddit data. Authors collected for each respective language were joined into a single panel. The mentions were then collated per author, and any authors whose statements indicated conflicting ages were removed from the panel. Here are a few example search terms that we used for this panel:
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| Reddit Panel - Gen X (EN, DE, ES, FR) | 375k | Mentions Search |
This panel contains Reddit authors that describe themselves with terms related to generation X in English, German, Spanish and French. We searched relevant age-related terms in authors’ posts and comments to infer if they are part of generation X. Authors were collected and assigned ages based on direct, precise mentions of age in their posts or comments within the last ten years of Reddit data. Authors collected for each respective language were joined into a single panel. The mentions were then collated per author, and any authors whose statements indicated conflicting ages were removed from the panel. Here are a few example search terms that we used for this panel:
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| Reddit Panel - Gen Y / Millennials (EN, DE, ES, FR) | 2.2M | Mentions Search |
This panel contains Reddit authors that describe themselves with terms related to millennials in English, German, Spanish and French. We searched relevant age-related terms in authors’ posts and comments to infer if they are a millennial. Authors were collected and assigned ages based on direct, precise mentions of age in their posts or comments within the last ten years of Reddit data. Authors collected for each respective language were joined into a single panel. The mentions were then collated per author, and any authors whose statements indicated conflicting ages were removed from the panel. Here are a few example search terms that we used for this panel:
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| Reddit Panel - Gen Z (EN, DE, ES, FR) | 1.4M | Mentions Search |
This panel contains Reddit authors that describe themselves with terms related to generation Z in English, German, Spanish and French. We searched relevant age-related terms in authors’ posts and comments to infer if they are part of generation Z. Authors were collected and assigned ages based on direct, precise mentions of age in their posts or comments within the last ten years of Reddit data. Authors collected for each respective language were joined into a single panel. The mentions were then collated per author, and any authors whose statements indicated conflicting ages were removed from the panel. Here are a few example search terms that we used for this panel:
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Reddit interest social panels
| Panel name | Number of authors | Creation method | Methodology |
|---|---|---|---|
| Reddit Interest - Animals | 190K | Author posting behavior |
This panel contains Reddit authors that repeatedly engage on subreddits related to the topic of Animals. We evaluated users' posting and commenting behaviors in order to infer their interest in this topic area. A Reddit user is added to the panel if they posted or commented on at least 3 separate threads on any subreddit related to the topic within a single month. Currently the panel was created by combining data from April, May and June 2022. Users displaying certain bot-like behaviours were excluded from the panel. Features considered to determine bot-like behaviour are as follows: author username contains word "bot", author username contains word "gpt", author is in top 0.01% of authors by post volume, author receives a relatively large number replies to their posts or comments which state "good bot" or "bad bot". Here are a few example subreddits that we used for this panel:
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| Reddit Interest - Arts and Design | 210K | Author posting behavior |
This panel contains Reddit authors that repeatedly engage on subreddits related to the topic of Arts and Design. We evaluated users' posting and commenting behaviors in order to infer their interest in this topic area. A Reddit user is added to the panel if they posted or commented on at least 3 separate threads on any subreddit related to the topic within a single month. Currently the panel was created by combining data from April, May and June 2022. Users displaying certain bot-like behaviours were excluded from the panel. Features considered to determine bot-like behaviour are as follows: author username contains word "bot", author username contains word "gpt", author is in top 0.01% of authors by post volume, author receives a relatively large number replies to their posts or comments which state "good bot" or "bad bot". Here are a few example subreddits that we used for this panel:
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| Reddit Interest - Automotive | 190K | Author posting behavior |
This panel contains Reddit authors that repeatedly engage on subreddits related to the topic of Automotive. We evaluated users' posting and commenting behaviors in order to infer their interest in this topic area. A Reddit user is added to the panel if they posted or commented on at least 3 separate threads on any subreddit related to the topic within a single month. Currently the panel was created by combining data from April, May and June 2022. Users displaying certain bot-like behaviours were excluded from the panel. Features considered to determine bot-like behaviour are as follows: author username contains word "bot", author username contains word "gpt", author is in top 0.01% of authors by post volume, author receives a relatively large number replies to their posts or comments which state "good bot" or "bad bot". Here are a few example subreddits that we used for this panel:
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| Reddit Interest - Business and Finance | 310K | Author posting behavior |
This panel contains Reddit authors that repeatedly engage on subreddits related to the topic of Business and Finance. We evaluated users' posting and commenting behaviors in order to infer their interest in this topic area. A Reddit user is added to the panel if they posted or commented on at least 3 separate threads on any subreddit related to the topic within a single month. Currently the panel was created by combining data from April, May and June 2022. Users displaying certain bot-like behaviours were excluded from the panel. Features considered to determine bot-like behaviour are as follows: author username contains word "bot", author username contains word "gpt", author is in top 0.01% of authors by post volume, author receives a relatively large number replies to their posts or comments which state "good bot" or "bad bot". Here are a few example subreddits that we used for this panel:
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| Reddit Interest - Entertainment | 1.6m | Author posting behavior |
This panel contains Reddit authors that repeatedly engage on subreddits related to the topic of Entertainment. We evaluated users' posting and commenting behaviors in order to infer their interest in this topic area. A Reddit user is added to the panel if they posted or commented on at least 3 separate threads on any subreddit related to the topic within a single month. Currently the panel was created by combining data from April, May and June 2022. Users displaying certain bot-like behaviours were excluded from the panel. Features considered to determine bot-like behaviour are as follows: author username contains word "bot", author username contains word "gpt", author is in top 0.01% of authors by post volume, author receives a relatively large number replies to their posts or comments which state "good bot" or "bad bot". Here are a few example subreddits that we used for this panel:
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| Reddit Interest - Family and Relationships | 910K | Author posting behavior |
This panel contains Reddit authors that repeatedly engage on subreddits related to the topic of Family and Relationships. We evaluated users' posting and commenting behaviors in order to infer their interest in this topic area. A Reddit user is added to the panel if they posted or commented on at least 3 separate threads on any subreddit related to the topic within a single month. Currently the panel was created by combining data from April, May and June 2022. Users displaying certain bot-like behaviours were excluded from the panel. Features considered to determine bot-like behaviour are as follows: author username contains word "bot", author username contains word "gpt", author is in top 0.01% of authors by post volume, author receives a relatively large number replies to their posts or comments which state "good bot" or "bad bot". Here are a few example subreddits that we used for this panel:
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| Reddit Interest - Food and Drink | 110K | Author posting behavior |
This panel contains Reddit authors that repeatedly engage on subreddits related to the topic of Food and Drink. We evaluated users' posting and commenting behaviors in order to infer their interest in this topic area. A Reddit user is added to the panel if they posted or commented on at least 3 separate threads on any subreddit related to the topic within a single month. Currently the panel was created by combining data from April, May and June 2022. Users displaying certain bot-like behaviours were excluded from the panel. Features considered to determine bot-like behaviour are as follows: author username contains word "bot", author username contains word "gpt", author is in top 0.01% of authors by post volume, author receives a relatively large number replies to their posts or comments which state "good bot" or "bad bot". Here are a few example subreddits that we used for this panel:
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| Reddit Interest - Gaming | 500K | Author posting behavior |
This panel contains Reddit authors that repeatedly engage on subreddits related to the topic of Gaming. We evaluated users' posting and commenting behaviors in order to infer their interest in this topic area. A Reddit user is added to the panel if they posted or commented on at least 3 separate threads on any subreddit related to the topic within a single month. Currently the panel was created by combining data from April, May and June 2022. Users displaying certain bot-like behaviours were excluded from the panel. Features considered to determine bot-like behaviour are as follows: author username contains word "bot", author username contains word "gpt", author is in top 0.01% of authors by post volume, author receives a relatively large number replies to their posts or comments which state "good bot" or "bad bot". Here are a few example subreddits that we used for this panel:
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| Reddit Interest - Healthy Living | 180K | Author posting behavior |
This panel contains Reddit authors that repeatedly engage on subreddits related to the topic of Gaming. We evaluated users' posting and commenting behaviors in order to infer their interest in this topic area. A Reddit user is added to the panel if they posted or commented on at least 3 separate threads on any subreddit related to the topic within a single month. Currently the panel was created by combining data from April, May and June 2022. Users displaying certain bot-like behaviours were excluded from the panel. Features considered to determine bot-like behaviour are as follows: author username contains word "bot", author username contains word "gpt", author is in top 0.01% of authors by post volume, author receives a relatively large number replies to their posts or comments which state "good bot" or "bad bot". Here are a few example subreddits that we used for this panel:
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| Reddit Interest - News and Education | 1.1m | Author posting behavior |
This panel contains Reddit authors that repeatedly engage on subreddits related to the topic of News and Education. We evaluated users' posting and commenting behaviors in order to infer their interest in this topic area. A Reddit user is added to the panel if they posted or commented on at least 3 separate threads on any subreddit related to the topic within a single month. Currently the panel was created by combining data from April, May and June 2022. Users displaying certain bot-like behaviours were excluded from the panel. Features considered to determine bot-like behaviour are as follows: author username contains word "bot", author username contains word "gpt", author is in top 0.01% of authors by post volume, author receives a relatively large number replies to their posts or comments which state "good bot" or "bad bot". Here are a few example subreddits that we used for this panel:
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| Reddit Interest - Sports | 460K | Author posting behavior |
This panel contains Reddit authors that repeatedly engage on subreddits related to the topic of Sports. We evaluated users' posting and commenting behaviors in order to infer their interest in this topic area. A Reddit user is added to the panel if they posted or commented on at least 3 separate threads on any subreddit related to the topic within a single month. Currently the panel was created by combining data from April, May and June 2022. Users displaying certain bot-like behaviours were excluded from the panel. Features considered to determine bot-like behaviour are as follows: author username contains word "bot", author username contains word "gpt", author is in top 0.01% of authors by post volume, author receives a relatively large number replies to their posts or comments which state "good bot" or "bad bot". Here are a few example subreddits that we used for this panel:
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| Reddit Interest - Style and Fashion | 160K | Author posting behavior |
This panel contains Reddit authors that repeatedly engage on subreddits related to the topic of Style and Fashion. We evaluated users' posting and commenting behaviors in order to infer their interest in this topic area. A Reddit user is added to the panel if they posted or commented on at least 3 separate threads on any subreddit related to the topic within a single month. Currently the panel was created by combining data from April, May and June 2022. Users displaying certain bot-like behaviours were excluded from the panel. Features considered to determine bot-like behaviour are as follows: author username contains word "bot", author username contains word "gpt", author is in top 0.01% of authors by post volume, author receives a relatively large number replies to their posts or comments which state "good bot" or "bad bot". Here are a few example subreddits that we used for this panel:
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| Reddit Interest - Technology and Computing | 340K | Author posting behavior |
This panel contains Reddit authors that repeatedly engage on subreddits related to the topic of Technology and Computing. We evaluated users' posting and commenting behaviors in order to infer their interest in this topic area. A Reddit user is added to the panel if they posted or commented on at least 3 separate threads on any subreddit related to the topic within a single month. Currently the panel was created by combining data from April, May and June 2022. Users displaying certain bot-like behaviours were excluded from the panel. Features considered to determine bot-like behaviour are as follows: author username contains word "bot", author username contains word "gpt", author is in top 0.01% of authors by post volume, author receives a relatively large number replies to their posts or comments which state "good bot" or "bad bot". Here are a few example subreddits that we used for this panel:
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| Reddit Interest - Television and Film | 360K | Author posting behavior |
This panel contains Reddit authors that repeatedly engage on subreddits related to the topic of Television and Film. We evaluated users' posting and commenting behaviors in order to infer their interest in this topic area. A Reddit user is added to the panel if they posted or commented on at least 3 separate threads on any subreddit related to the topic within a single month. Currently the panel was created by combining data from April, May and June 2022. Users displaying certain bot-like behaviours were excluded from the panel. Features considered to determine bot-like behaviour are as follows: author username contains word "bot", author username contains word "gpt", author is in top 0.01% of authors by post volume, author receives a relatively large number replies to their posts or comments which state "good bot" or "bad bot". Here are a few example subreddits that we used for this panel:
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| Reddit Interest - Travel | 570K | Author posting behavior |
This panel contains Reddit authors that repeatedly engage on subreddits related to the topic of Travel. We evaluated users' posting and commenting behaviors in order to infer their interest in this topic area. A Reddit user is added to the panel if they posted or commented on at least 3 separate threads on any subreddit related to the topic within a single month. Currently the panel was created by combining data from April, May and June 2022. Users displaying certain bot-like behaviours were excluded from the panel. Features considered to determine bot-like behaviour are as follows: author username contains word "bot", author username contains word "gpt", author is in top 0.01% of authors by post volume, author receives a relatively large number replies to their posts or comments which state "good bot" or "bad bot". Here are a few example subreddits that we used for this panel:
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