This dataset is about companies in Catano. It has 1 row. It features 3 columns: employees, and Facebook link.

This dataset is about companies in Astoria. It has 161 rows. It features 3 columns: employees, and Facebook link.

This dataset is about companies. It has 203,841 rows and is filtered where the sector is Information Technology. It features 3 columns: employees, and Facebook link.

Facebook is becoming an essential tool for more than just family and friends. Discover how Cheltenham Township (USA), a diverse community just outside of Philadelphia, deals with major issues such as the Bill Cosby trial, everyday traffic issues, sewer I/I problems and lost cats and dogs. And yes, theft.

Communities work when they're connected and exchanging information. What and who are the essential forces making a positive impact, and when and how do conversational threads get directed or misdirected?

Use Any Facebook Public Group

You can leverage the examples here for any public Facebook group. For an example of the source code used to collect this data, and a quick start docker image, take a look at the following project: facebook-group-scrape.

Data Sources

There are 4 csv files in the dataset, with data from the following 5 public Facebook groups:

• Unofficial Cheltenham Township
• Elkins Park Happenings!
• Free Speech Zone
• Cheltenham Lateral Solutions
• Cheltenham Township Residents

post.csv

These are the main posts you will see on the page. It might help to take a quick look at the page. Commas in the msg field have been replaced with {COMMA}, and apostrophes have been replaced with {APOST}.

• gid Group id (5 different Facebook groups)
• pid Main Post id
• id Id of the user posting
• name User's name
• timeStamp
• shares
• url
• msg Text of the message posted.
• likes Number of likes

comment.csv

These are comments to the main post. Note, Facebook postings have comments, and comments on comments.

• gid Group id
• pid Matches Main Post identifier in post.csv
• cid Comment Id.
• timeStamp
• id Id of user commenting
• name Name of user commenting
• rid Id of user responding to first comment
• msg Message

like.csv

These are likes and responses. The two keys in this file (pid,cid) will join to post and comment respectively.

• gid Group id
• pid Matches Main Post identifier in post.csv
• cid Matches Comments id.
• response Response such as LIKE, ANGRY etc.
• id The id of user responding
• name Name of the user responding

member.csv

These are all the members in the group. Some members never, or rarely, post or comment. You may find multiple entries in this table for the same person. The name of the individual never changes, but they change their profile picture. Each profile picture change is captured in this table. Facebook gives users a new id in this table when they change their profile picture.

• gid Group id
• id Id of the member
• name Name of the member
• url URL of the member

This dataset is about companies in Chipata. It has 1 row. It features 3 columns: employees, and Facebook link.

The number of Facebook users in the United States was forecast to continuously increase between 2024 and 2028 by in total 12.6 million users (+5.04 percent). After the ninth consecutive increasing year, the Facebook user base is estimated to reach 262.8 million users and therefore a new peak in 2028. Notably, the number of Facebook users of was continuously increasing over the past years.User figures, shown here regarding the platform facebook, have been estimated by taking into account company filings or press material, secondary research, app downloads and traffic data. They refer to the average monthly active users over the period and count multiple accounts by persons only once.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).

OverviewThe BuzzFeed dataset, officially known as the BuzzFeed-Webis Fake News Corpus 2016, comprises content from 9 news publishers over a 7-day period close to the 2016 US election. It was created to analyze the spread of misinformation and hyperpartisan content on social media platforms, particularly Facebook.Dataset CompositionNews Articles: The dataset includes 1,627 articles from various sources:826 from mainstream publishers256 from left-wing publishers545 from right-wing publishersFacebook Posts: Each article is associated with Facebook post data, including metrics like share counts, reaction counts, and comment counts.Comments: The dataset includes nearly 1.7 million Facebook comments discussing the news content.Fact-Check Ratings: Each article was fact-checked by professional journalists at BuzzFeed, providing veracity assessments.Key FeaturesPublisher Information: The dataset covers 9 publishers, including 6 hyperpartisan (3 left-wing and 3 right-wing) and 3 mainstream outlets.Temporal Aspect: The data was collected over seven weekdays (September 19-23 and September 26-27, 2016).Verification Status: All publishers included in the dataset had earned Facebook's blue checkmark, indicating authenticity and elevated status.Metadata: Includes various metrics such as publication dates, post types, and engagement statistics.Potential ApplicationsThe BuzzFeed dataset is valuable for various research and analytical purposes:News Veracity Assessment: Researchers can use machine learning techniques to classify articles based on their factual accuracy.Social Media Analysis: The dataset allows for studying how news spreads on platforms like Facebook, including engagement patterns.Hyperpartisan Content Study: It enables analysis of differences between mainstream and hyperpartisan news sources.Content Strategy Optimization: Media companies can use insights from the dataset to refine their content strategies.Audience Analysis: The data can be used for demographic analysis and audience segmentation.This dataset provides a comprehensive snapshot of news dissemination and engagement on social media during a crucial period, making it a valuable resource for researchers, data scientists, and media analysts studying online information ecosystems.

Die Studie über Facebook-Nutzer wurde von infratest dimap im Auftrag der Konrad-Adenauer-Stiftung durchgeführt. Im Erhebungszeitraum 26. November bis 4. Dezember 2018 wurden 2.041 Facebook-Nutzer in Onlineinterviews (CAWI) zu folgenden Themen befragt: Internetnutzung, Facebook-Gruppen, Facebooknutzung, politische Inhalte auf Facebook, Reaktion auf Inhalte, Bildexperiment und Sonntagsfrage. Die Auswahl der Befragten erfolgte durch eine Quotenstichprobe aus einem Online-Access-Panel. Nutzung verschiedener Internetangebote (Tinder, Facebook, Twitter, snapchat, Instagram, YouTube, Online-Zeitungen, nichts davon); Nutzung offener oder geschlossener Facebook-Gruppen; Facebook-Inhalte zu politischen Themen, zu berufsbezogenen Themen, zu Hobbies, zur Unterhaltung bzw. zu anderen Themen; Art der Facebook-Nutzung (lese/ like/ teile Inhalte, schreibe Kommentare, verbreite eigene Inhalte); politische Facebook-Nutzung (lese/ like/ teile politische Inhalte, schreibe Kommentare zu politischen Themen, verbreite eigenen Inhalt zu politischen Themen); Reaktion auf Facebook- Inhalte bzw. Kommentare (fühle mich informiert, unterhalten, verärgert, provoziert); Zustimmung zu verschiedenen Aussagen zu Facebook (auf Facebook regen mich andere auf, zeige ich anderen ihre Grenzen, kann ich anonym meine Meinung sagen, finde ich viele verschiedene Meinungen, finde ich Meinungen, die sonst unterdrückt werden, traue ich mich Dinge zu sagen/ teilen, die ich sonst nicht sagen würde); Parteipräferenz (Sonntagsfrage); Kommentar (offen) zu einem provozierenden Bild (Split A: Flüchtlinge, Split B: Pegida). Demographie: Geschlecht; Alter (Geburtsjahr); Bildung; Erwerbstätigkeit; berufliche Stellung; Haushaltsnettoeinkommen (gruppiert); Bundesland. Zusätzlich verkodet wurde: lfd. Nummer; Gewichtungsfaktor. The study on Facebook users was conducted by infratest dimap on behalf of the Konrad Adenauer Foundation. During the survey period from November 26 to December 4, 2018, 2,041 Facebook users were surveyed in online interviews (CAWI) on the following topics: internet use, Facebook groups, Facebook use, political content on Facebook, reaction to content, image experiment and Sunday question. Respondents were selected by quota sampling from an online access panel. Use of various internet services (Tinder, Facebook, Twitter, snapchat, Instagram, YouTube, online newspapers, none of the above); use of open or closed Facebook groups; Facebook content on political topics, on job-related topics, on hobbies, on entertainment or on other topics; type of Facebook use (read/ like/ share content, write comments, disseminate own content); political Facebook use (read/ like/ share political content, write comments on political topics, disseminate own content on political topics); reaction to Facebook content or comments (do I feel informed, entertained, annoyed, provoked, etc.). comments (feel informed, entertained, annoyed, provoked); agreement with various statements on Facebook (on Facebook others upset me, I show others their limits, I can speak my mind anonymously, I find many different opinions, I find opinions that are otherwise suppressed, I dare to say/ share things I would not otherwise say); party preference (Sunday question); comment (open) on a provocative image (split A: refugees, split B: Pegida). Demography: sex; age (year of birth); education; employment; occupational status; net household income (grouped); federal state. Additionally coded: serial number; weighting factor.

This dataset is about companies in Brasília. It has 215 rows. It features 3 columns: employees, and Facebook link.

Analysis of ‘Predicting Facebook Posts Impact ’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/yamqwe/predicting-facebook-posts-impact on 13 February 2022.

--- Dataset description provided by original source is as follows ---

About this dataset

• The data is related to posts' published during the year of 2014 on the Facebook's page of a renowned cosmetics brand. This dataset contains 500 of the 790 rows and part of the features analyzed by Moro et al. (2016). It includes 7 features known prior to post-publication and 12 features for evaluating post-impact along with other Techincal information such as:
• Is it an Image or a Status
• Time & Date
• and more.

How to use this dataset

• Estimate how to post the most impactful facebook post
• More datasets

Acknowledgements

If you use this dataset in your research, please credit The Author

--- Original source retains full ownership of the source dataset ---

Which county has the most Facebook users?

              There are more than 378 million Facebook users in India alone, making it the leading country in terms of Facebook audience size. To put this into context, if India’s Facebook audience were a country then it would be ranked third in terms of largest population worldwide. Apart from India, there are several other markets with more than 100 million Facebook users each: The United States, Indonesia, and Brazil with 193.8 million, 119.05 million, and 112.55 million Facebook users respectively.

              Facebook – the most used social media

              Meta, the company that was previously called Facebook, owns four of the most popular social media platforms worldwide, WhatsApp, Facebook Messenger, Facebook, and Instagram. As of the third quarter of 2021, there were around 3,5 billion cumulative monthly users of the company’s products worldwide. With around 2.9 billion monthly active users, Facebook is the most popular social media worldwide. With an audience of this scale, it is no surprise that the vast majority of Facebook’s revenue is generated through advertising.

              Facebook usage by device
              As of July 2021, it was found that 98.5 percent of active users accessed their Facebook account from mobile devices. In fact, almost 81.8 percent of Facebook audiences worldwide access the platform only via mobile phone. Facebook is not only available through mobile browser as the company has published several mobile apps for users to access their products and services. As of the third quarter 2021, the four core Meta products were leading the ranking of most downloaded mobile apps worldwide, with WhatsApp amassing approximately six billion downloads.

As part of official investigations, government officials sometimes request data about people who use Facebook. The vast majority of these requests relate to criminal cases, such as robberies or kidnappings. In many of these cases, the government is requesting basic subscriber information, such as name and length of service. This report contain information requested by governments to Facebook.

This dataset is about companies in Mauritania. It has 41 rows. It features 3 columns: employees, and Facebook link.

Gain valuable insights with our comprehensive Social Media Dataset, designed to help businesses, marketers, and analysts track trends, monitor engagement, and optimize strategies. This dataset provides structured and reliable social media data from multiple platforms.

Dataset Features

User Profiles: Access public social media profiles, including usernames, bios, follower counts, engagement metrics, and more. Ideal for audience analysis, influencer marketing, and competitive research. Posts & Content: Extract posts, captions, hashtags, media (images/videos), timestamps, and engagement metrics such as likes, shares, and comments. Useful for trend analysis, sentiment tracking, and content strategy optimization. Comments & Interactions: Analyze user interactions, including replies, mentions, and discussions. This data helps brands understand audience sentiment and engagement patterns. Hashtag & Trend Tracking: Monitor trending hashtags, topics, and viral content across platforms to stay ahead of industry trends and consumer interests.

Customizable Subsets for Specific Needs Our Social Media Dataset is fully customizable, allowing you to filter data based on platform, region, keywords, engagement levels, or specific user profiles. Whether you need a broad dataset for market research or a focused subset for brand monitoring, we tailor the dataset to your needs.

Popular Use Cases

Brand Monitoring & Reputation Management: Track brand mentions, customer feedback, and sentiment analysis to manage online reputation effectively. Influencer Marketing & Audience Analysis: Identify key influencers, analyze engagement metrics, and optimize influencer partnerships. Competitive Intelligence: Monitor competitor activity, content performance, and audience engagement to refine marketing strategies. Market Research & Consumer Insights: Analyze social media trends, customer preferences, and emerging topics to inform business decisions. AI & Predictive Analytics: Leverage structured social media data for AI-driven trend forecasting, sentiment analysis, and automated content recommendations.

Whether you're tracking brand sentiment, analyzing audience engagement, or monitoring industry trends, our Social Media Dataset provides the structured data you need. Get started today and customize your dataset to fit your business objectives.

As of April 2024, Facebook had an addressable ad audience reach 131.1 percent in Libya, followed by the United Arab Emirates with 120.5 percent and Mongolia with 116 percent. Additionally, the Philippines and Qatar had addressable ad audiences of 114.5 percent and 111.7 percent.

The number of Facebook users in Europe was forecast to continuously increase between 2024 and 2028 by in total 15.5 million users (+3.91 percent). According to this forecast, in 2028, the Facebook user base will have increased for the sixth consecutive year to 412.26 million users. User figures, shown here regarding the platform facebook, have been estimated by taking into account company filings or press material, secondary research, app downloads and traffic data. They refer to the average monthly active users over the period and count multiple accounts by persons only once.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the number of Facebook users in countries like South America and North America.

As of April 2024, it was found that men between the ages of 25 and 34 years made up Facebook largest audience, accounting for 18.4 percent of global users. Additionally, Facebook's second largest audience base could be found with men aged 18 to 24 years.

              Facebook connects the world

              Founded in 2004 and going public in 2012, Facebook is one of the biggest internet companies in the world with influence that goes beyond social media. It is widely considered as one of the Big Four tech companies, along with Google, Apple, and Amazon (all together known under the acronym GAFA). Facebook is the most popular social network worldwide and the company also owns three other billion-user properties: mobile messaging apps WhatsApp and Facebook Messenger,
              as well as photo-sharing app Instagram. Facebook usersThe vast majority of Facebook users connect to the social network via mobile devices. This is unsurprising, as Facebook has many users in mobile-first online markets. Currently, India ranks first in terms of Facebook audience size with 378 million users. The United States, Brazil, and Indonesia also all have more than 100 million Facebook users each.

Facebook, the most widely used social media platform, has been adopted by public health organisations for health promotion and behaviour change campaigns and activities. However, limited information is available on the most effective and efficient use of Facebook for this purpose. This study sought to identify the features of Facebook posts that are associated with higher user engagement on Australian public health organisations’ Facebook pages. We selected 20 eligible pages through a systematic search and coded 360-days of posts for each page. Posts were coded by: post type (e.g., photo, text only etc.), communication technique employed (e.g. testimonial, informative etc.) and use of marketing elements (e.g., branding, use of mascots). A series of negative binomial regressions were used to assess associations between post characteristics and user engagement as measured by the number of likes, shares and comments. Our results showed that video posts attracted the greatest amount of user engagement, although an analysis of a subset of the data suggested this may be a reflection of the Facebook algorithm, which governs what is and is not shown in user newsfeeds and appear to preference videos over other post types. Posts that featured a positive emotional appeal or provided factual information attracted higher levels of user engagement, while conventional marketing elements, such as sponsorships and the use of persons of authority, generally discouraged user engagement, with the exception of posts that included a celebrity or sportsperson. Our results give insight into post content that maximises user engagement and begins to fill the knowledge gap on effective use of Facebook by public health organisations.

Full edition for scientific use. The AUTNES dataset on party Facebook pages contains information on parties’ Facebook posts during the six weeks of election campaign for the Austrian general election in 2013. Data collection took place in autumn 2015. We retrieved posts for all parties that passed the threshold for entering the parliament in 2013. Each post constitutes a unit of analysis. The coding procedure applies the AUTNES relational approach of recording subjects, predicates, and objects to party Facebook pages. The subject is the party or candidate that operates the Facebook page and is coded with the name (if an individual is present), organisational affiliation and appearance in the coding unit (text only, text and image, image only). There are two types of objects: issues and object actors. Issues are recorded by coders selecting from the AUTNES issue coding scheme the dominant policy issue and the dominant campaign issue in the coding unit. The issue predicate numerically records whether the subject’s position towards the policy issue is one of support, rejection, or conveys a neutral/ambivalent stance. Up to ten object actors are recorded from each coding unit in the same way as the subject actor, supplemented with an evaluation by the subject actor (positive, negative, or neutral). In addition to the basic subject–predicate–object structure we code several additional variables: character traits, party records as well as a description of every actor’s outfit. Moreover, the dataset contains variables describing the Facebook page, the coding unit as well as images and calls for (preference) votes or campaign participation. Variables: Variables referring to Facebook posting: URL; type of Facebook page (party or candidate page); timestamp (date when the posting was published); text of the posting; links that were published in the posting; hashtags; number of likes, comments and shares of the posting; variables referring to posting: technical problems with coding; call for vote (for the author of the page); call for a preference vote with the name of the respective candidate; call for campaign participation in general and on Facebook; content of the posting: continuous text, picture, video; variables referring to the author of the Facebook page: author’s organization; author’s name; mention of the author in the posting; author’s outfit; author’s characteristics; author’s record; variables referring to issues: campaign issue; predicate; policy issue; reference to policy issue at the EU level; variables referring to object actors: object actor presence; object actor’s name; object actor’s organisation; appearance; predicate; object actor’s outfit; reference to the coded campaign issue and to the coded policy issue; object actor’s characteristics; object actor’s record; number of additional object actors that were not coded; variables referring to pictures: pictures of individuals that were not coded as object actors; description of individuals; number of people; reference to a party.

App Reviews

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1842206%2Fd4a6033b6bd31af45d5175d02e697934%2FAPPLEAPPS2.png?generation=1700357122842963&alt=media" alt="">

1. uber-request-a-ride-us- 73787 rows
2. waze-navigation-live-traffic-us- 26260 rows
3. facebook-us- 24200 rows
4. spotify-music-and-podcasts-us- 15580 rows
5. netflix-us- 11760 rows
6. pinterest-us- 10860 rows
7. X-us- 8160 rows
8. tiktok-us- 2542 rows
9. tinder-dating-chat-friends-us- 1060 rows
10. instagram-us- 300 rows

These reviews are from Apple App Store

Usage

This dataset should paint a good picture on what is the public's perception of the apps over the years. Using this dataset, we can do the following

1. Extract sentiments and trends
2. Identify which version of an app had the most positive feedback, the worst.
3. Use topic modelling to identify the pain points of the application.

(AND MANY MORE!)

Note

Images generated using Bing Image Generator