How we did this

Pew Research Center conducted this study to better understand how many parents visit online communities where other parents discuss their experiences raising children, and the sorts of issues they discuss there. It is based on a representative survey of U.S. parents and an analysis of six months of data from Reddit’s largest parenting forum, r/Parenting.

For the survey component of this analysis, we surveyed 3,054 parents who have children ages 12 and under from May 13 to 26, 2025. The survey sample includes respondents from two different sources: Pew Research Center’s American Trends Panel (ATP) and SSRS’s Opinion Panel (OP). The ATP and OP are both groups of people recruited through national, random sampling of residential addresses who have agreed to take surveys regularly. This kind of recruitment gives nearly all U.S. adults a chance of selection.

Interviews were conducted either online or by telephone with a live interviewer. The survey is weighted to be representative of parents or guardians of children ages 12 and under by gender, race, ethnicity, partisan affiliation, education and other factors. Read more about the ATP’s methodology.

For the Reddit analysis, we collected all user submissions and comments on the r/Parenting subreddit from Jan. 17 to July 17, 2025, using the Reddit Data API. The resulting dataset contains 29,295 posts and 853,209 comments posted during that period.

For each post, we determined:

• Whether the emotions expressed in the post were on balance positive or negative
• If the post mentioned any of three topics of interest (division of child care responsibilities between parents, family finances and children’s technology use)
• Whether the comments replying to the original post were supportive or not

Reddit post excerpts in this report have been edited for clarity and concision, and to remove personally identifiable details.

Here are the questions and topline for the survey portion of the report. The methodology contains more information about the survey, how we collected and classified Reddit data, and how we validated the results of our analysis.

Terminology

On Reddit, a subreddit is a discussion page that focuses on a specific subject. Members of a subreddit can write a post or submission for other users to read and respond to. “Post” and “submission” are used interchangeably in this report.

Other users can reply to submissions with a comment. “Top-level” comments are those that respond directly to the original submission, rather than comments that reply to another comment.

For the survey component of this report, “parents of a child age 12 or younger” and “parents” refer to U.S. adults who are parents or guardians of at least one child age 12 or younger. Parents may also have children in other age groups.

As today’s parents navigate the challenges of raising a child, many are turning to online spaces where fellow parents share their experiences. One such space is the r/Parenting community on Reddit. It is the largest community for parents on the site, with more than 8 million members as of November 2025.

To better understand the discussions about parenting that take place online, we examined six months of user submissions and comments on the r/Parenting subreddit. We also conducted a survey of U.S. parents with a child age 12 or younger to ask about their experiences with online parenting communities.

Here are some of the main findings: 

Posts on r/Parenting frequently mention kids’ technology use and the division of parental duties.

Reddit users can write posts (also called “submissions”) that other users are able to read and respond to. Posts on the r/Parenting subreddit cover a wide range of concerns. For this study, we focused on those mentioning three key issues:

• 23% of all posts mentioned the division of child care responsibilities between parents.
• 18% mentioned kids’ technology use.
• 13% mentioned family finances or the financial challenges of raising a child.

In total, 44% of all posts on r/Parenting mentioned one or more of these issues.

Parents often turn to these online communities in times of distress.

Some 48% of all posts written during our six-month study period expressed mostly negative emotions, often describing concerns or seeking advice for a stressful dilemma. Just 5% of posts expressed mainly positive emotions, such as those celebrating a developmental milestone or recounting a success story.

Of the topics we looked at, posts mentioning the division of child care duties between parents were especially likely to be framed in a negative way.

Commenters are there to help.

Despite longstanding advice to “never read the comments,” we found that the comments responding to these Reddit posts are overwhelmingly supportive and contribute usefully to discussions. 

A majority of the accounts that commented during these six months did so multiple times. This highlights how online spaces for parents can provide a dedicated and supportive community to reach out to in the face of specific challenges.

Moms are especially likely to look online for advice from other parents.  

In our survey of U.S. parents, 34% say they visit places online where other parents talk about their experiences raising children at least monthly. And 42% of mothers say they do this regularly, nearly double the share among fathers (22%).

An analysis of the r/Parenting subreddit

To learn more about parenting discussions taking place online, we analyzed all the user submissions and comments posted to the r/Parenting subreddit from January to July 2025. This amounted to around 30,000 posts and 850,000 comments in total.

Issues people discuss on r/Parenting

Discussions on r/Parenting address a wide range of topics. Posters frequently ask for advice, share recent parenting experiences or pose questions to the Reddit community. For this analysis, we looked for three specific topics that appear frequently in user submissions:

• Division of child care responsibilities between parents
• Children’s use of technology
• Financial challenges of raising children

In total, 44% of all posts published during our six-month study period mention one or more of these issues, with division of parenting responsibilities the most common. Below is a more in-depth look at how often and in what contexts these topics are discussed. (Appendix A contains a more detailed list of the terms that distinguish each topic.)

Division of parenting duties (mentioned in 23% of all posts): Frequent themes in these posts include stay-at-home parenthood, co-parenting between separated parents and balancing domestic work with a career outside the home.

For example, the following excerpts are adapted from r/Parenting posts mentioning shared parenting responsibilities.

Children’s technology use (18% of all posts): Posts mentioning this topic are distinguished by discussions of devices and screen time, TV, social media like YouTube and TikTok, and popular video games for young people like Minecraft or Roblox. Read our October 2025 study for survey findings on how parents manage screen time for their kids.

The following excerpts are adapted from r/Parenting posts mentioning children’s technology use.

Financial challenges of parenthood and raising children (13% of all posts): Common themes in these posts include general discussions of budgeting, costs and affordability, as well as how to navigate significant expenses like rent, tuition, mortgages and paying off debts. Read our 2022 study for more on the economic challenges faced by U.S. parents.

The following excerpts are adapted from r/Parenting posts mentioning the financial challenges of raising children.

Positive and negative emotions in posts on r/Parenting

When we examined the emotions expressed in r/Parenting posts, we found that 48% convey negative emotions like anger, sadness, disgust, stress or fear.

A similar share of posts express neutral or mixed emotions. This includes posts that do not clearly express any emotions, as well as those with a roughly even mix of positive and negative emotions.

Posts that contain mainly positive emotions like gratitude, pride, joy or amusement are much rarer. Just 5% of posts express these positive sentiments.

Certain posts are more likely to be negative than others.

For instance, 59% of the most popular posts (those with the most comments and upvotes) express primarily negative emotions.

And of the topics we measured, posts that mention the division of parenting responsibilities are by far the most negative. Around two-thirds of all posts mentioning this topic (68%) express negative emotions. For the other topics we looked at, that share is roughly half.

Support and criticism in r/Parenting comments

Although negative emotions are quite common in r/Parenting posts, comments in direct reply to these posts are overwhelmingly supportive.

Of the top-level comments that we collected over this six-month period – that is, those replying directly to the original post and not to another comment – 88% offered support for the person who made the original post. These include comments offering helpful advice, responding thoughtfully to a question posed in the original post, or otherwise contributing positively to the community discussion.

By contrast, just 12% of comments are not supportive of the original post or its author. These include comments that are difficult to interpret or irrelevant to the original post, those that provide a mix of advice and criticism, and those that are outright critical.

Other findings about posting and commenting behavior on r/Parenting

Our analysis uncovered several other findings that shed light on the use of online parenting communities.

Users on r/Parenting comment more often than they post. During our six-month study period, over 110,000 unique accounts authored a post or a comment on r/Parenting. The vast majority of these accounts (94%) left a comment, while 20% wrote a post.

Those who comment tend to do so repeatedly, with 59% of commenters writing multiple comments over the six months. (By comparison, 16% of post authors submitted multiple times in the same period.) Commenting is highly concentrated among a small share of users: The top 5% of commenters produced around half (52%) of all comments.

Toddlers and young children are a frequent subject of discussion. On Reddit, users submitting a post can tag that post with a “flair” to indicate the topic of discussion. Among the posts tagged with a child age group in r/Parenting, 20% are tagged “Toddler 1-3 years,” and a similar share (23%) are tagged “Child 4-9 years.”

Posts on r/Parenting often get deleted or removed. As of October 2025, just 62% of the posts we collected were still accessible on the site. Some 29% were deleted by the post author, while 9% were removed by the subreddit moderators.

Survey findings: How U.S. parents use and view online parenting communities

Online parenting communities can take many forms. To learn more about the average parent’s experience, we surveyed U.S. parents with at least one child age 12 or younger about online spaces where parents talk about raising children. We asked them to think about their experiences with platforms like social media and online discussion forums.

Our survey finds that 34% of parents say they visit online parenting communities at least monthly. Another 34% say they rarely visit them, while 33% say they never do.

Majorities of parents in nearly every major demographic group say they visit online parenting communities at least rarely. And certain groups are especially likely to do so at least monthly:

• Mothers: 42% of mothers and 22% of fathers regularly do this, a difference of 20 percentage points.
• Younger parents: 45% of parents ages 18 to 29 visit these sites regularly. By comparison, 31% of parents ages 30 to 49 visit online parenting communities regularly, as do just 17% of parents ages 50 and older.
• Newer parents: Almost half (47%) of parents whose oldest child is under 5 visit these communities regularly.¹

How parents feel about online parenting communities

Among those who ever visit online parenting communities (even if only rarely), 63% say these spaces make them feel more informed about being a parent. And about half (48%) say online communities make them feel more connected to other parents.

But these experiences are not universally positive: 38% say parenting communities make them feel more overwhelmed because of all the information they need to know. And sizable shares say these communities make them feel less informed and less connected to other parents.

How many parents post or comment on these sites?

Among parents who ever visit online parenting communities, 40% say they have posted or commented about their own experiences as a parent. But only 5% say they do this often.

Mothers are more likely to engage in the discussion than fathers are. Some 46% of mothers who visit online parenting communities say they ever post or comment, compared with 30% of fathers.

This report is a collaborative effort based on the input and analysis of the following individuals:

Primary researchers

Anna Lieb, Computational Social Science Assistant
Athena Chapekis, Computational Social Science Analyst
Sono Shah, Associate Director, Data Labs
Aaron Smith, Director, Data Labs
Sofia Conway, Qualitative Analysis Intern
Sawyer Reed, Research Assistant

Research team

Devin Teehan, Former Qualitative Analysis Intern

Editorial and graphic design

Alissa Scheller, Senior Information Graphics Designer
Anna Jackson, Editorial Specialist

Communications and web publishing

Julia O’Hanlon, Communications Manager
Sogand Afkari, Communications Manager
Talia Price, Communications Associate
Janakee Chavda, Associate Digital Producer

In addition, the project benefited greatly from the guidance of Colleen McClain, Monica Anderson and Courtney Kennedy.

This report is based on two different data sources: a representative survey of U.S. parents and Reddit data from the r/Parenting subreddit.

The American Trends Panel survey methodology

Overview

Data in this report comes from Wave 171 of the American Trends Panel (ATP), Pew Research Center’s nationally representative panel of randomly selected U.S. adults. The survey was conducted from May 13 to 26, 2025, among a sample of adults who are parents or guardians of any child age 12 or under. A total of 3,054 eligible parents responded out of 6,287 who were sampled, for a survey-level response rate of 60% (AAPOR RR3).² This includes 1,697 respondents from the ATP and an additional 1,357 from the SSRS Opinion Panel (OP).

The cumulative response rate accounting for nonresponse to the recruitment surveys and attrition is 2%. The break-off rate among panelists who logged on to the survey and completed at least one item is 1%. The margin of sampling error for the full sample of 3,054 respondents is plus or minus 2.2 percentage points.

SSRS conducted the survey for Pew Research Center via online (n=2,935) and live telephone (n=119) interviewing. Interviews were conducted in both English and Spanish.

To learn more about the ATP, read “About the American Trends Panel.”³

Panel recruitment

Since 2018, the ATP has used address-based sampling (ABS) for recruitment. A study cover letter and a pre-incentive are mailed to a stratified, random sample of households selected from the U.S. Postal Service’s Computerized Delivery Sequence File. This Postal Service file has been estimated to cover 90% to 98% of the population.⁴ Within each sampled household, the adult with the next birthday is selected to participate. Other details of the ABS recruitment protocol have changed over time but are available upon request.⁵ Prior to 2018, the ATP was recruited using landline and cellphone random-digit-dial surveys administered in English and Spanish.

A national sample of U.S. adults has been recruited to the ATP approximately once per year since 2014. In some years, the recruitment has included additional efforts (known as an “oversample”) to improve the accuracy of data for underrepresented groups. For example, Hispanic adults, Black adults and Asian adults were oversampled in 2019, 2022 and 2023, respectively.

Sample design

The overall target population for this survey was noninstitutionalized persons ages 18 and older living in the United States who are the parent or guardian of any child 12 or under. All active ATP members who had previously indicated they were the parent or guardian of any child 12 or under were invited to participate in this wave.

The ATP was supplemented with a sample from SSRS’s Opinion Panel. For the OP sample, SSRS took a probability proportional to size (PPS) sample of OP panelists with children 0 to 17 years, then screened respondents for selection. Only OP panelists who were parents or guardians of any child 12 or under were screened into the survey.

At the start of the survey, potentially eligible respondents were asked a series of screening questions to confirm their eligibility to complete the survey. For the ATP and OP samples, respondents were considered eligible if they indicated they were the parent or guardian of any child 12 or under.

Questionnaire development and testing

The questionnaire was developed by Pew Research Center in consultation with SSRS. The web program used for online respondents was rigorously tested on both PC and mobile devices by the SSRS project team and Center researchers. The SSRS project team also populated test data that was analyzed in SPSS to ensure the logic and randomizations were working as intended before launching the survey.

Incentives

All respondents were offered a post-paid incentive for their participation. ATP and OP respondents may receive the post-paid incentive in the form of a check or gift code to online merchants such as Amazon.com, Target.com or Walmart.com. Incentive amounts ranged from $5 to $15 for ATP respondents, and $5 to $10 for OP respondents, depending on whether the respondent belongs to a part of the population that is harder or easier to reach. Differential incentive amounts were designed to increase panel survey participation among groups that traditionally have low survey response propensities.

Data collection protocol

The data collection field period for this survey was May 13 to 26, 2025. Surveys were conducted via self-administered web survey or by live telephone interviewing. 

For panelists who take surveys online:⁶ Postcard notifications were mailed to a subset of ATP panelists on May 12.⁷ Survey invitations were sent out in two separate launches: soft launch and full launch. 427 panelists were included in the soft launch (60 from ATP, 367 from OP), which began with an initial invitation sent on May 13. All remaining English- and Spanish-speaking sampled online panelists were included in the full launch and were sent an invitation on May 14.

Panelists participating online were sent an email invitation. ATP panelists received up to four email reminders if they did not respond to the survey, and OP panelists received up to two email reminders if they did not respond to the survey. ATP panelists who consented to SMS messages were sent an SMS invitation with a link to the survey and up to four SMS reminders. SSRS panelists who consented to SMS messages were sent an SMS invitation with a link to the survey and up to two SMS reminders.

For panelists who take surveys over the phone with a live interviewer: Prenotification postcards were mailed to ATP panelists on May 9. Soft launch took place on May 13 and involved dialing until a total of four interviews had been completed. All remaining English- and Spanish-speaking sampled phone panelists’ numbers were dialed throughout the remaining field period. Panelists who take surveys via phone can receive up to six calls from trained SSRS interviewers.

Data quality checks

To ensure high-quality data, Center researchers performed data quality checks to identify any respondents showing patterns of satisficing. This includes checking for whether respondents left questions blank at very high rates or always selected the first or last answer presented. As a result of this checking, no respondents were removed from the survey dataset prior to weighting and analysis.

Weighting

The ATP data is weighted in a process that accounts for multiple stages of sampling and nonresponse that occur at different points in the panel survey process. First, each panelist begins with a base weight that reflects their probability of recruitment into the panel. Base weights for OP respondents were provided by SSRS. The base weights for ATP and OP respondents were combined and scaled to account for the sample design.

The combined base weights were calibrated to align with the following estimated benchmarks for the population of parents or guardians of children ages 12 and under: age, gender, education, race/ethnicity, years living in the U.S. (among foreign born), volunteerism, voter registration, frequency of internet use, religious affiliation, party affiliation, census region, metropolitan status, the number of children ages 0 to 4, the number of children ages 5 to 12, and the number of children ages 13 to 17.

Because there are no official benchmarks for this population, weighting parameters were estimated using the eligible respondents to Wave 171 from the ATP sample. First, all ATP respondents who completed the screening questions on Wave 171, regardless of final eligibility, were weighted to match the full set of ATP members who were sampled on the following dimensions: age, gender, education, race/ethnicity, years living in the U.S. (among foreign born), volunteerism, voter registration, frequency of internet use, religious affiliation, party affiliation, census region and metropolitan status. These weights were then used to calculate weighting parameters based only on ATP respondents to Wave 171 who screened as eligible.

In the final step, the weights were trimmed at the 1st and 99th percentiles to reduce the loss in precision stemming from variance in the weights. Sampling errors and tests of statistical significance take into account the effect of weighting.

The following table shows the unweighted sample sizes and the error attributable to sampling that would be expected at the 95% level of confidence for different groups in the survey.

Sample sizes and sampling errors for other subgroups are available upon request. In addition to sampling error, one should bear in mind that question wording and practical difficulties in conducting surveys can introduce error or bias into the findings of opinion polls.

Dispositions and response rates

How family income tiers are calculated

Family income data reported in this study is adjusted for household size and cost-of-living differences by geography. Panelists then are assigned to income tiers that are based on the median adjusted family income of all American Trends Panel members. The process uses the following steps:

1. First, panelists are assigned to the midpoint of the income range they selected in a family income question that was measured on either the most recent annual profile survey or, for newly recruited panelists, their recruitment survey. This provides an approximate income value that can be used in calculations for the adjustment.
2. Next, these income values are adjusted for the cost of living in the geographic area where the panelist lives. This is calculated using price indexes published by the U.S. Bureau of Economic Analysis. These indexes, known as Regional Price Parities (RPP), compare the prices of goods and services across all U.S. metropolitan statistical areas as well as non-metro areas with the national average prices for the same goods and services. The most recent data available at the time of the annual profile survey is from 2022. Those who fall outside of metropolitan statistical areas are assigned the overall RPP for their state’s non-metropolitan area.
3. Family incomes are further adjusted for the number of people in a household using the methodology from Pew Research Center’s previous work on the American middle class. This is done because a four-person household with an income of say, $50,000, faces a tighter budget constraint than a two-person household with the same income.
4. Panelists are then assigned an income tier. “Middle-income” adults are in families with adjusted family incomes that are between two-thirds and double the median adjusted family income for the full ATP at the time of the most recent annual profile survey. The median adjusted family income for the panel is roughly $74,100. Using this median income, the middle-income range is about $49,400 to $148,200. Lower-income families have adjusted incomes less than $49,400 and upper-income families have adjusted incomes greater than $148,200 (all figures expressed in 2023 dollars and scaled to a household size of three). If a panelist did not provide their income and/or their household size, they are assigned “no answer” in the income tier variable.

Two examples of how a given area’s cost-of-living adjustment was calculated are as follows: the Pine Bluff metropolitan area in Arkansas is a relatively inexpensive area, with a price level that is 19.1% less than the national average. The San Francisco-Oakland-Berkeley metropolitan area in California is one of the most expensive areas, with a price level that is 17.9% higher than the national average. Income in the sample is adjusted to make up for this difference. As a result, a family with an income of $40,400 in the Pine Bluff area is as well off financially as a family of the same size with an income of $58,900 in San Francisco. 

The respondents from the SSRS Opinion Panel oversample answered the same family income and household size questions, and their incomes were adjusted using the procedures detailed above. They were then assigned an income tier based on the median adjusted family income for the full ATP at the time of the most recent annual profile survey.

Reddit data collection and analysis

This report analyzes posts and comments from the r/Parenting forum on Reddit. It is based on a total of 29,295 posts (also known as “submissions”) and 853,209 comments posted on r/Parenting from Jan. 17 to July 17, 2025. Post and comment text were classified using OpenAI’s GPT-4.1 mini model. Details about data collection, classification and model performance are discussed below.

Reddit data collection

Reddit posts, comments and engagement metrics from the r/Parenting subreddit were collected using requests to the official Reddit Data API. We ran the Reddit data collection pipeline on an hourly schedule from Jan. 17 to July 17, 2025. Each hour, we collected the following:

• All Reddit submissions posted to r/Parenting in the past hour, including the submission author, title and body text. We also collected metadata such as the time it was posted and the tag used to categorize the post (known as a “flair” on Reddit).
• Comments on all Reddit submissions posted to r/Parenting 48 hours earlier, including the comment text, author and upvote count. We also collected metadata such as the time it was posted and whether the comment was a reply to the original post or a reply to another comment.
• Engagement metrics for all Reddit submissions posted to r/Parenting 48 hours earlier, including the number of comments, upvote score (number of upvotes minus downvotes) and upvote ratio (the ratio of upvotes to total votes).

For example, let’s say a submission was posted to r/Parenting on Jan. 17 at 7:40 a.m. This post would be automatically collected at the next scheduled hourly collection (8:00 a.m.), and its comments and engagement metrics would be collected at the hourly collection 48 hours later (8:00 a.m. on Jan. 19).

On Feb. 21, two hours of data collection were disrupted by a brief sitewide Reddit outage.

A Reddit submission status audit was conducted about nine months after the start of our data collection period. On Oct. 16, 2025, we made a request to the Reddit Data API for every submission in our original dataset to check whether the submission status was active, deleted or removed.

Language and time zone of r/Parenting posts and comments

Over 99% of posts in r/Parenting are written in English. English language was detected for all posts using the stringi R package’s function for detecting character set and language, with an English confidence cutoff of 0.3.

Additionally, the subreddit is most active during the daytime in U.S. time zones. Based on the timestamps available for the submissions and comments in our dataset, the most common times to post were between 10 a.m. and 2 p.m. Eastern time. Meanwhile, the least common times to post were between 2 a.m. and 6 a.m. Eastern time.

Post classification

To better understand discourse on r/Parenting, each Reddit post in our dataset was classified based on the emotions expressed and topics mentioned in the post. Researchers worked with qualitative coding interns to develop a codebook that describes these categories and accurately reflects some themes that commonly appear in posts on r/Parenting.

After finalizing the category labels and definitions, two qualitative analysis interns labeled a sample of 700 Reddit posts. Due to the relatively sparse occurrence of some labels, this sample included a random sample of posts and an oversample of posts that contained relevant keywords or flairs. The validation dataset of 700 posts included the following balance of class labels:

• Emotion label: 337 negative, 89 positive and 274 neutral posts
• Topic labels:
  • 148 posts that mention family finances, 552 that do not
  • 120 posts that mention unequal division of labor, 580 that do not
  • 146 posts that mention children’s technology use, 554 that do not

A summary of the labels, their definitions and an inter-rater reliability metric are available in the table below. In the case of conflicts between coders, a member of the research team selected a winning label for the final ground truth dataset.

After labeling the validation dataset of 700 Reddit posts, we used OpenAI’s GPT-4.1 mini model to classify all 29,295 Reddit posts in the full dataset. For each post, we prompted the model with annotation instructions, a description of each label (taken from the codebook used by human annotators), and the title and body of the Reddit post. For six posts in the dataset, the model did not provide a valid label; these six posts were included in our analysis with an “unknown” label, but the unknown share rounded to 0% for all calculations. The full model prompt text is available in Appendix B. The model’s performance metrics are available in the table below.

Comment classification

In addition to Reddit posts, we also classified comments to learn more about the community of commenters on r/Parenting. In the six-month data collection period, we collected a total of 853,209 comments replying to the set of 29,295 posts. As noted in the data collection section above, our comment dataset only includes comments that were posted within 48 hours of the original post.

We observed that many posts in r/Parenting include explicit requests for advice, information or sympathy, and discourse on the subreddit largely takes place in the comments that respond and react to these posts. To assess the community response to posts on r/Parenting, we classified a comment as “supportive” if it thoughtfully or helpfully replies to the original post. This includes comments that offer helpful advice, respond to a question posed in the post or otherwise contribute positively to the community discussion.

It should be noted that by this definition, “supportive” does not require that the comment agrees with the original post; for example, constructive criticism or a respectful disagreement still counts as supportive if it contributes positively to the conversation and replies helpfully to the original post. On the other hand, comments that have a disrespectful tone, criticize the original post or author, are off-topic, or are difficult to interpret would be classified as “not supportive.”

For this comments analysis, we focused only on comments that replied directly to the original post, also known as top-level comments. Since a Reddit comment may be posted as a reply to other comments, it is common for lengthy comment threads to develop into discussions that may be only adjacently related to the original post.

Out of the 853,209 comments in our full dataset, 475,311 of those comments were valid top-level comments. Valid top-level comments include comments that satisfy the following criteria:

• The comment replies to the original post, rather than replying to another comment.
• The comment author is not the same user as the original post author.
• The comment author is not a r/Parenting subreddit moderator (i.e., the author username is not “AutoModerator” or “Parenting-ModTeam”).
• The comment was not deleted by the user or removed by Reddit.

To create a ground truth dataset for comment classification, two qualitative coding interns labeled a sample of 1,005 top-level comments as “supportive” or “not supportive.” Due to the sparse occurrence of unsupportive comments, this sample included a random sample of comments and an oversample of comments that were likely to be not supportive. The oversample of likely unsupportive comments was selected using an early version of the classification prompt to a large language model.

The qualitative coders reached 92% agreement on the comments ground truth dataset (Cohen’s kappa = 0.624). In the case of conflicts between coders, a member of the research team selected a winning label for the final validation dataset. The validation dataset of 1,005 posts included 881 supportive comments and 124 unsupportive comments.

We used OpenAI’s GPT-4.1 mini model to classify all 475,311 valid top-level comments in the full dataset. For each request to the model, the input prompt included annotation instructions and a description of the “supportive” and “not supportive” label. It also included the Reddit post text and the text of up to five corresponding comments to be classified. The full model prompt text is available in Appendix B. Based on the human-annotated ground truth dataset, the model achieved 87% accuracy, with a weighted average F1 score of 0.876, precision score of 0.886 and a recall score of 0.868. Of all 475,311 valid top-level comments in the dataset, 102 comments could not be classified due to errors parsing the model output.

All 29,925 Reddit posts in our dataset were classified by mentions of three topics: family finances, technology use, and division of labor. We used a pointwise mutual information (PMI) metric to identify terms that are associated with posts mentioning each topic. Distinctive terms for each topic are listed in the table below.

For this report, Reddit posts and comments were classified using the following prompts to GPT-4.1 mini. The prompts were designed to mirror the codebooks that our research team used to create the validation datasets of human-annotated posts and comments. In the prompt templates below, italics indicate input text that varies based on the post or comment being classified.

Post emotion classification prompt

You are a social science researcher tasked with assigning emotional valence labels to a dataset.

You will receive the text of a Reddit submission on the r/Parenting subreddit forum. Designate the emotional valence expressed by the parent who wrote the post as either POSITIVE, NEGATIVE, or NEUTRAL in alignment with the following codebook:

POSITIVE posts include: Strong expressions of gratitude, pride, joy, or amusement OR Celebratory sentiments OR Posts with mixed emotions that overall lean positive. On their own, neutral descriptions of a child’s preferences, a child having fun or holiday celebrations do not count; this label only applies if the parent explicitly expresses positive emotion.

NEGATIVE posts include: Strong expressions of anger, sadness, disgust, stress, or fear OR Posts with mixed emotions that overall lean negative. Posts seeking advice for challenging situations are very common in this subreddit, and not all of these posts should be counted as NEGATIVE. Please use this label only for posts that explicitly describe the negative emotions that the post author is experiencing.

NEUTRAL posts include: Telling a story, asking for advice, or sharing other information without suggesting a strong emotion from the author OR Posts that show mixed emotions and it is unclear whether the post leans overall more positive or negative. Posts that show a parent’s concern but which do not express a strongly positive or negative emotion (i.e., other than practical concern) should be classified as NEUTRAL.

The label should apply to the emotion expressed by the parent who wrote the post, not the child’s emotion.

Special note about the NEUTRAL label:

Use the NEUTRAL label liberally. This is often the best choice for posts that don’t show strong expressions of emotion one way or the other. Some posts may describe a fortunate or unfortunate situation but do not explicitly express a positive or negative emotion from the parent who authored the post. Posts like this should be labeled as NEUTRAL. For example, a parent may post something like: “My child often has tantrums when we try to get her to eat peas, because she doesn’t like peas. Do you have any tips for how to get her to eat?” This post describes a common challenge in parenting but doesn’t use overly emotional language. Therefore, it should be labeled as NEUTRAL. However, if the post specifically said, “My child often has tantrums when we try to get her to eat peas, because she doesn’t like peas. I’m getting really worried about it. Do you have any tips for how to get her to eat?” then it would be NEGATIVE.

Please categorize the emotion of the provided Reddit post. Reply only with one of the three specified responses: POSITIVE, NEGATIVE, or NEUTRAL. Do not respond with any additional text before or after.

TITLE: <title of post to be classified>

<body text of the post to be classified>

Post topic classification prompt

You are a social science researcher tasked with assigning topic labels to a dataset.

You will receive the text of a Reddit submission on the r/Parenting subreddit forum. Based on the Reddit submission, you will assign three topic labels to the Reddit post. The three topics are finances, division of labor, and technology. The three topic labels are defined as follows.

*** FINANCES TOPIC: ***

Description: These posts contain discussions of family finances or costs related to raising a child.

If the finance topic is present in the Reddit post, assign the label MENTIONS_FINANCES.

If not, assign the label DOES_NOT_MENTION_FINANCES.

For example, the finances topic includes:

– Budgeting for parenting needs

– Child care and education costs

– Complaints about high prices of parenting expenses

– Money-saving tips

The finances topic label does NOT include:

– Family finances that do not relate to child care costs or the material comfort of a child (e.g., a post about an aunt who can’t afford their electricity bill, but that doesn’t have any impact on a child/parent relationship mentioned in the post)

– Children’s access to money, unless it relates to the family’s finances (e.g., a post about children’s allowance would NOT count, but a post about a parent struggling to afford an allowance for their child WOULD count)

– Mentions of events that may have financial impacts, but these financial impacts are not mentioned in the post (e.g., a post about identity theft in which the possible financial impacts such as credit score or bank fraud are NOT mentioned would NOT count)

– Posts that mention a purchase or a price WITHOUT discussing affordability or expressing a judgment about whether the cost was too high or too low (e.g., a post that says, “We are taking the kids on a cruise to Miami. The cruise tickets were $1,000 each and cover six days of travel. Do you have any travel tips for bringing kids on a cruise?” would NOT count)

*** DIVISION OF LABOR TOPIC: ***

Description: These posts mention unequal share of child care responsibilities between parents, or delegation of different child care responsibilities between parents.

If the division of labor topic is present in the Reddit post, assign the label MENTIONS_LABOR.

If not, assign the label DOES_NOT_MENTION_LABOR.

For example, the division of labor topic includes:

– Navigating co-parenting responsibilities, where the child splits time between parents with custody

– One parent having more decision-making power than the other

– Unequal division of household chores (Note that this does not necessarily have to be negative: e.g., “I stay at home and take on child care while my spouse works and goes grocery shopping” would count, even if it’s in a positive or neutral tone)

– Other mentions of navigating shared responsibility of child care

The division of labor topic label does NOT include:

– Sharing responsibilities between people who are not directly responsible for the child (e.g., a grandparent, a nanny, etc.)

– Appreciation posts that describe the efforts or work of another parent (e.g., “My husband took out the trash today! I’m so proud.” would NOT count)

– Disagreements between parents about child care decisions, especially when the disagreement does not indicate any power imbalance or unequal parental responsibility between parents (e.g., “I want my kid to eat Cheerios, but my spouse doesn’t like to feed them Cheerios. Who do you think is right?” would NOT count)

– Single parents or divorced parents talking about their day-to-day parenting life, without explicit mentions of an absent/slacking co-parent (e.g. “I’m a stay-at-home mom who feels overwhelmed.” would NOT count, since no partner is mentioned. But “I’m a stay-at-home mom and my husband doesn’t help me enough” would count)

– Division of labor between a child and their parent, or a child doing chores around the house

*** TECHNOLOGY TOPIC: ***

Description: These posts contain mentions of children’s use of digital technology. 

If the children’s use of technology topic is present in the Reddit post, assign the label MENTIONS_TECH.

If not, assign the label DOES_NOT_MENTION_TECH.

For example, the technology topic includes mentions of:

– Children’s use of smart phones, tablets, laptops, smartwatches, etc.

– Kids using social media

– Kids’ screen time, managing kids’ screen time, and screen time as a punishment or reward

– Children playing video games

– Cyberbullying & child safety online

– Kids’ use of AI and AI chatbots, such as for schoolwork or for entertainment

– The technology label can apply to a post that does not feature digital technology as the main focus. But the mention of technology should be substantive, even if it is a minor part. See the “does not include” section below.

The technology topic label does NOT include:

– Any parental device usage

– Mentions of technology where the child’s access to technology is irrelevant to the story, concern, or advice given in the post. (e.g., A conversation that took place on a cell phone, where access to the device itself was not a factor in the conversation or the ability to conduct that conversation, would NOT count.)

Note: For each topic described above, any mention of the topic should be considered; it does not have to be the central focus of the post. In fact, many mentions of these topics may occur as a small part of a longer and more wide-ranging post.

Please categorize the topics of the provided Reddit post using the topic definitions provided above. A Reddit post may mention multiple topics described above, or it could mention none of them. Reply with a structured JSON-formatted output, where the key is the name of the topic and the value is the selected label for that topic. For example, a valid output would look like:

{“FINANCES”: “MENTIONS_FINANCES”, “DIVISION_OF_LABOR”: “MENTIONS_LABOR”, “TECHNOLOGY”: “DOES_NOT_MENTION_TECH”}

TITLE: <title of post to be classified>

<body text of the post to be classified>

Comment supportiveness classification prompt

You are a research assistant tasked with assigning labels to a dataset of Reddit comments. You will receive the text of a Reddit post from the r/Parenting subreddit, followed by up to 5 comments replying to the post. For each comment, you will decide whether the comment is SUPPORTIVE or CRITICAL of the original post. It might be helpful to consider: If you were the original poster and you received the comment, would your reaction be positive or negative?

You will label each comment with one of three labels: SUPPORTIVE, MIXED, or CRITICAL. The labels are defined as follows:

– Mark the comment as SUPPORTIVE if the post author would likely feel supported by this comment. The comment may satisfy any of the following:

    – Helpfully address or validate the main ideas of the original post and/or contribute to the discussion in a helpful way

    – Provide advice as asked for by the OP in a constructive or helpful manner

    – Express support, enthusiasm, and other positive emotions towards the original post

    – Provide constructive criticism or a respectful disagreement

    – Empathize, for example by sharing a similar experience

    – Note that a SUPPORTIVE comment does not have to *agree* with the original post author, especially if the post solicits advice or encourages discourse/debate! As mentioned above, a SUPPORTIVE comment may thoughtfully disagree with the original post or provide constructive criticism.

– Mark the comment as CRITICAL if the post author would likely feel criticized by this comment. The comment may satisfy any of the following:

    – Expresses disapproval of the original post (or the original post author), without expressing empathy or understanding

    – Does not help address concerns in the original post, or addresses the post but does not use a helpful or constructive tone

    – Criticizes the post author, without any constructive or helpful spin

    – Gives critical feedback to the post author when the post does not solicit advice

    – Uses a rude, disrespectful, or mean-spirited tone

    – Lodges a personal attack on the post author or their child, or criticizes the post author’s personal ability to be a good parent

– Mark the comment as MIXED if it’s unclear whether the post author would feel supported or criticized by this comment. The comment may:

    – Offer unsolicited advice that may be helpful, but which is not relevant to the original post

    – Offer advice that addresses the original post and provides commentary that may be helpful, but which also criticizes the parent. These “harsh advice”-style comments may use a negatively judgmental, snarky or firm tone (rather than a friendly or empathetic tone)

    – Be off-topic, difficult to understand, nonsense/gibberish, or too brief to suggest a supportive or critical tone

    – Express an even mix of both supportive and critical attributes

– Mark the comment as NA if the comment text is [deleted], [removed by Reddit], [comment by OP] or similar.

Note that comments phrased as clarifying questions can be difficult to categorize. The label depends on how the question was asked: Does it use a tone that sounds like the comment is making a genuine attempt to understand, listen, and/or address the original post? If so, it may be SUPPORTIVE. On the other hand, does it use a tone that’s sarcastic or throws into question the validity of the original post? If so, it may be CRITICAL.

Use your best judgement and the definitions supplied above to mark each comment as SUPPORTIVE, CRITICAL, or MIXED. In particular, don’t hesitate to use the MIXED label for comments that have both critical and supportive elements. The input text format will look something like this:

Title: Do you think kids should get braces?

Submission text:

I don’t want to spend $3,000 on braces. Is it really necessary?

—– Comment 1 with ID: aaaaaaa —–

Yes, braces are good for long-term health.

—– Comment 2 with ID: bbbbbbb —–

I don’t think you need it, I never had braces and I’m totally fine.

—– Comment 3 with ID: ccccccc —–

I can’t believe there are parents on here who wouldn’t get braces for their kid.

—– Comment 4 with ID: ddddddd —–

You didn’t provide enough information, you’re not gonna get good advice if we don’t know how bad your kid’s teeth are. That being said, I’d say it’s probably worth it to get braces in most cases.

—– Comment 5 with ID: eeeeeee —–

I understand that it’s a big investment, but I really think it pays off in the long run to get braces.

The output should be formatted as a structured JSON output that includes the comment index, comment ID and label for each comment. Using the example input Reddit text above, the output would look like:

[

    {

        “comment_index”: 1,

        “comment_id”: “aaaaaaa”,

        “label”: “SUPPORTIVE”

    },

    {

        “comment_index”: 2,

        “comment_id”: “bbbbbbb”,

        “label”: “SUPPORTIVE”

    },

    {

        “comment_index”: 3,

        “comment_id”: “ccccccc”,

        “label”: “CRITICAL”

    },

    {

        “comment_index”: 4,

        “comment_id”: “ddddddd”,

        “label”: “MIXED”

    },

    {

        “comment_index”: 5,

        “comment_id”: “eeeeeee”,

        “label”: “SUPPORTIVE”

    }

]

Note that the input text may contain fewer than 5 comments. If this is the case, then please only include the available comments in the output JSON list.

Title: <post title>

Submission text: <post body text>

—– Comment 1 with ID: <comment ID> —–

<comment body text>

—– Comment 2 with ID: <comment ID> —–

<comment body text>

—– Comment 3 with ID: <comment ID> —–

<comment body text>

—– Comment 4 with ID: <comment ID> —–

<comment body text>

—– Comment 5 with ID: <comment ID> —–

<comment body text>