![\"Tracing](\"https:\/\/usersearch.org\/updates\/wp-content\/uploads\/2021\/11\/tracking-people-on-twitter-1024x1024.webp\"){kind=tracking}
We are going to show you how to determine a Twitter user’s core network of friends and track them. You’re also going to be able to work out who their best friends are and their likely Geolocation. You may even be able to work out their real identity, habits, relationships, and motivations. Finally, we’ll show you how much money one of their tweets can be sold for.<\/p>\n\n\n\n
For the purposes of the exercises here, we use our own Twitter account. You can too (https:\/\/twitter.com\/Usersearch_web)<\/a>, or use your own.<\/p>\n\n\n\n We cover 12 useful steps on how to pretty much map out a person’s personal, and professional interests, just by how they use Twitter. More importantly, who they use Twitter, with. Indeed what we show you may appear to be too revealing, but rest assured we only use public information.<\/p>\n\n\n\n First, you need to have an overall good feel and understanding of the account you are interested in. So, first, visit TruthNest (https:\/\/app.truthnest.com\/), log in with your Twitter account, and enter your target username (without @) in the “Twitter Screen Name” field.<\/p>\n\n\n\n After that, the service generates a report at the top of the page you can find the following information:<\/p>\n\n\n\n Subsequently, in the \u201cActivity\u201d tab it\u2019s possible to find out what languages prevail in tweets, what applications and mobile operating systems are used for posting, as well as which users and websites the account has linked to recently.<\/p>\n\n\n\n Similarly, there is also a list of the most frequently used hashtags, a graph of activity by time of day and days of the week.<\/p>\n\n\n\n Under “Network” you can see the number of following\/followers, the average growth rate of the audience, and the “important” followers (those with the most followers).<\/p>\n\n\n\n Also, the service evaluates the quality of subscribers, showing which part of them has a suspiciously low (“dead souls”) or suspiciously high activity (“bots”).<\/p>\n\n\n\n Finally, in the Influence section, you can see the average number of likes and retweets, their distribution by week, and which popular people have linked to the account and written something in the comments.<\/p>\n\n\n\n This information is enough to get a general idea about the subject and the degree of influence of the account. Now let’s move on to the more in-depth stages of the investigation.<\/p>\n\n\n\n In addition to TruthNest, there are many web applications with similar functionality. For example:<\/p>\n\n\n\n You can try different services and choose the one that seems most convenient to you.<\/p>\n\n\n\n Service Tweet Topic Explorer (tweettopicexplorer.neoformix.com) allows you to visually see which words are used most often in a user’s tweets.<\/p>\n\n\n\n If you click on one of the colored circles, you will see a list of tweets that mention a certain word on the left side of the screen.<\/p>\n\n\n\n Pay special attention to the red colored circles in the center. They will tell you in a few seconds what a person’s most important interests are.<\/p>\n\n\n\n It\u2019s possible to download a user’s tweets to your computer to analyze them manually. To do this, you need to enter the user’s name at https:\/\/www.vicinitas.io\/free-tools\/download-user-tweets<\/u> and click the button \u201cExport to Excel\u201d.<\/p>\n\n\n\n Only up to 3,200 tweets can be downloaded. This is due to the limitations of the free version of the Twitter API.<\/p>\n\n\n\n After you download the tweet file, you can open it in your favorite spreadsheet editor and search for interesting information in it. But, here and later in the article, I will show examples of data analysis in a table using the Google Sheets function as an example.<\/p>\n\n\n\n Google Sheets (“Edit” -> “Find and Replace”) even supports regular expressions (be sure to check the box). The figure shows an example of a search for all emails in column B.<\/p>\n\n\n\n For this purpose, the following sequence of characters was used as the key word: ([a-zA-Z0-9+._-]+@[a-zA-Z0-9._-]+\\.[a-zA-Z0-9_-]+)<\/p>\n\n\n\n (http|ftp|https):\\\/\\\/([\\w_-]+(?:(?:\\.[\\w_-]+)+))([\\w.,@?^=%&:\\\/~+#-]*[\\w@?^=%&\\\/~+#-])<\/p>\n\n\n\n And this regular expression comes in handy for finding URLs in the text of tweets. I found it on Stackoverflow, there are a lot of detailed answers to questions about solving various problems with regular expressions.<\/p>\n\n\n\n An OSINT expert does not need to know the syntax of regular expressions (although that would be great).<\/p>\n\n\n\n For all sorts of needs (searching for phone numbers of different countries, bank card numbers, IP addresses, etc.) there are complete ready-made regular expressions that you can just copy and use.<\/p>\n\n\n\n You can find them in numerous free libraries. For example https:\/\/regexr.com\/<\/u><\/a>.<\/p>\n\n\n\n By the way, If you don’t use Google Tables, you can just copy the text of the tweets on Regexr.com and do regular expression searches directly on the site.<\/p>\n\n\n\n You don’t have to download tweets to find any information. You can do it directly on Twitter using advanced search operators.<\/p>\n\n\n\n Examples:<\/strong><\/p>\n\n\n\n You can find the most popular tweets by filtering by the minimum number of likes and retweets:<\/p>\n\n\n\n You can also filter tweets by content type. For example:<\/p>\n\n\n\n Don’t forget that all of these search operators can be combined with each other, as well as using “AND”, “OR” and “-” (to exclude tweets matching certain criteria from search results).<\/p>\n\n\n\n If you don’t want to remember the search operators, you can just use the normal “Advanced search” on Twitter. (https:\/\/twitter.com\/search-advanced)<\/p>\n\n\n\n We are done with collecting information about the user. Now, let’s move on to the analysis of the social circles. Subscriptions, followers, and people with whom he argues in the comments. If you are lucky, you may find his relatives, colleagues, close friends, and worst enemies among them.<\/p>\n\n\n\n Vicintas.io (https:\/\/www.vicinitas.io\/free-tools\/download-twitter-followers<\/u>) can download part (<3200) of Twitter account\u2019s followers and export it to Excel\/Google Sheets.<\/p>\n\n\n\n A variety of tools can now be used to investigate them. First, don’t forget about the regular expressions described in step 3 to search for emails and other contact information.<\/p>\n\n\n\n We can also use the “detectlanguage()” function to analyze the “Bio” column and determine which languages are spoken by the followers of the account.<\/p>\n\n\n\n To find out which countries and cities prevail among the account’s followers, you can copy the text from the “Location” column in the Text Analyzer<\/p>\n\n\n\n (https:\/\/www.online-utility.org\/text\/analyzer.jsp<\/u>) and calculate the specificity of words (in our case, place names).<\/p>\n\n\n\n The “Location” column, however, is not a good example of using frequency analysis of words. It would be better to analyze the “Bio” column.<\/p>\n\n\n\n After all, you can see how subscribers are distributed by city and country on the world map using the Followerwonk service.<\/p>\n\n\n\n One of the main purposes of analyzing lists of subscribers\/subscribers is to highlight people who may be closest to the target under study. Same names (relatives), working in the same company, living in the same city (especially if it is small), etc.<\/p>\n\n\n\n One of the main purposes of analyzing lists of subscribers\/subscribers is to highlight people who may be closest to the target under study. Same names (relatives), working in the same company, living in the same city (especially if it is small), etc.<\/p>\n\n\n\n But it often happens that nothing in their profile indicates the intimacy of the two people, although they are constantly communicating.<\/p>\n\n\n\n Chirpty.com (https:\/\/chirpty.com\/) analyzes the frequency of mentions and public communication with different users and produces three lists: closest circle, close circle, and far circle.<\/p>\n\n\n\n To learn as much as you can about your target, you need to take each account in your inner circle in turn and take a closer look at what connects them. Below are a couple of services for this purpose. Use the “to:” filter to find all responses addressed to a specific account. For example:<\/p>\n\n\n\n To leave only replies (no mentions), you can add “filter: replies”<\/strong> or, conversely, remove them by adding the same filter with a minus sign.<\/p>\n\n\n\n If two accounts have participated in a discussion with many participants and many threads of dialogue, then use https:\/\/treeverse.app\/ to clearly see “who is talking to whom and when”.<\/p>\n\n\n\n Tweetbeaver helps to find accounts followed by one user that also followed by another user. <\/p>\n\n\n\n It\u2019s possible to display on screen or download as CSV detailed information about these accounts (name, bio, location, biography, creation date, ID).<\/p>\n\n\n\n This file, again, can be opened in Google Sheets and analyzed with regular expressions, “detectlanguage()”, etc.<\/p>\n\n\n\n Followewonk allows one to compare the followers of two accounts and see how their audiences overlap.<\/p>\n\n\n\n If two accounts have few subscribers (<200), but their audiences overlap by more than 40%, it’s very likely that they belong to the same person.<\/p>\n\n\n\n Unfortunately, this service is suitable for accounts with a small number of followers (up to 5000). For more popular Twitter users, only part of their audience will be taken into account in the analysis.<\/p>\n\n\n\n And https:\/\/doesfollow.com<\/u> will help to instantly check if one user is subscribed to another.<\/p>\n\n\n\n Copy the link to the Twitter account into the main field at https:\/\/cipher387.github.io\/quickcacheandarchivesearch\/<\/u> and get quick access to old versions of the account page in the search engine caches and various web archives (a total of 27 services).<\/p>\n\n\n\n This way you can find old versions of the biography of the account, now hidden links to profiles in other social networks deleted tweets.<\/p>\n\n\n\n Above all, this trick comes in handy for those who are researching Twitter accounts to buy ads from them. The Twitter Money Calculator (https:\/\/influencermarketinghub.com\/twitter-money-calculator\/) will help you estimate the approximate cost per tweet, taking into account the size of the audience and its engagement.<\/p>\n\n\n\n Similar data is shown by Webfluental.<\/p>\n\n\n\n This price is an estimate. For accounts with entertainment themes, it may be 2-3 times lower than this, and for professional, highly specialized blogs, on the contrary, 2-3 times higher.<\/p>\n\n\n\n The most important things to find in a Twitter account is this:<\/p>\n\n\n\n Additional information about all of them can be collected using usersearch.org<\/a>. It finds emails, profiles in social networks, dating sites, forums of various topics, leaks databases, etc.<\/p>\n\n\n\n The maximum number of services to check the existence of the user with a certain nickname is available with a premium subscription.<\/a><\/p>\n\n\n\n Dozens of services have been developed to collect Twitter account data, but in this text, we have only gone through the most basic ones, which help you to find out the most important things quickly and for free.<\/p>\n\n\n\n This article could be called an ‘Introduction to Twitter OSINT’ and is not meant to give the reader the most comprehensive guide, but simply as an introduction and inspiration to explore different methods and tools.<\/p>\n\n\n\n The process of analyzing tweets can be automated and there are many tools for this. The most famous is the Python library Twint (https:\/\/github.com\/twintproject\/twint). This allows you to write scripts to automatically gather biographical information about a user, search for tweets using regular expressions and search operators (while saving the results to CSV), scrape a list of following and followers.<\/p>\n\n\n\n Twint is not too difficult to learn and will be useful for anyone who regularly analyzes Twitter accounts. However, all of its features are also available in the web services described above in this article.<\/p>\n\n\n\n \u200b\u200bAnd if you need to solve some particularly complex and unique research problems, you can always turn to the Twitter Developer API (https:\/\/developer.twitter.com\/en\/docs\/twitter-api) to create your own application.<\/p>\n","protected":false},"excerpt":{"rendered":" Analysing a person’s Twitter account is a very important step in the process of gathering general information about them. Twitter may not advertise extra details on the user profiles. But, data analysis and thanks to the public nature of how Twitter stores user profile communication, and the relationships, we have some tricks for you. We […]<\/p>\n","protected":false},"author":1,"featured_media":2321,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""}},"footnotes":""},"categories":[1],"tags":[32,50],"class_list":["post-1021","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-blog","tag-osint","tag-twitter"],"yoast_head":"\nWhat can Twitter tell you about a person?<\/h2>\n\n\n\n
1. Overall account analysis<\/h2>\n\n\n\n
![\"\"](\"https:\/\/usersearch.org\/updates\/wp-content\/uploads\/2021\/11\/Finding-users-on-Twitter1.webp\")
![\"Checking](\"https:\/\/usersearch.org\/updates\/wp-content\/uploads\/2021\/11\/image-13-1024x443-11.webp\")
Twitter Activity<\/h3>\n\n\n\n
![\"The](\"https:\/\/usersearch.org\/updates\/wp-content\/uploads\/2021\/11\/image-15-1024x498.jpg\")
![\"The](\"https:\/\/usersearch.org\/updates\/wp-content\/uploads\/2021\/11\/image-16-1024x579.jpg\")
2. Content analysis of tweets<\/h2>\n\n\n\n
![\"Content](\"https:\/\/usersearch.org\/updates\/wp-content\/uploads\/2021\/11\/image-18-1024x450-1.webp\")
3. Analyze tweets with regular expressions<\/h2>\n\n\n\n
![\"Find](\"https:\/\/usersearch.org\/updates\/wp-content\/uploads\/2021\/11\/image-19-1024x443-1.webp\")
![\"Download](\"https:\/\/usersearch.org\/updates\/wp-content\/uploads\/2021\/11\/image-20-1024x462-1.webp\")
![\"\"](\"https:\/\/usersearch.org\/updates\/wp-content\/uploads\/2021\/11\/image-21-1024x614-1.webp\")
![\"regex](\"https:\/\/usersearch.org\/updates\/wp-content\/uploads\/2021\/11\/image-22-1024x410-1.webp\")
4. Analyze tweets with search operators<\/h2>\n\n\n\n
![\"Using](\"https:\/\/usersearch.org\/updates\/wp-content\/uploads\/2021\/11\/image-23-1024x381-1.webp\")
![\"](\"https:\/\/usersearch.org\/updates\/wp-content\/uploads\/2021\/11\/image-24-1024x711-1.webp\")
5. Analyzing account followers<\/h2>\n\n\n\n
![\"Reviewing](\"https:\/\/usersearch.org\/updates\/wp-content\/uploads\/2021\/11\/image-25-1024x438-1.webp\")
![\"\"](\"https:\/\/usersearch.org\/updates\/wp-content\/uploads\/2021\/11\/image-26-1024x482-1.webp\")
![\"witter](\"https:\/\/usersearch.org\/updates\/wp-content\/uploads\/2021\/11\/image-27-1024x505-1.webp\")
6. View the geolocation of the account subscribers on the map<\/h2>\n\n\n\n
![\"Geolocation](\"https:\/\/usersearch.org\/updates\/wp-content\/uploads\/2021\/11\/image-28-1024x509-1.webp\")
<\/a>7. Determine the accounts with which the target interacts most often<\/h2>\n\n\n\n
![\"Working](\"https:\/\/usersearch.org\/updates\/wp-content\/uploads\/2021\/11\/image-29-1024x710-1.webp\")
<\/p>\n\n\n\n8. Analyzing the interaction between two Twitter users<\/h2>\n\n\n\n
![\"Interaction](\"https:\/\/usersearch.org\/updates\/wp-content\/uploads\/2021\/11\/image-30-1024x481-1.webp\")
![\"Relationships](\"https:\/\/usersearch.org\/updates\/wp-content\/uploads\/2021\/11\/image-31-1024x424-1.webp\")
9. Comparing the audiences of the two accounts<\/h2>\n\n\n\n
![\"Finding](\"https:\/\/usersearch.org\/updates\/wp-content\/uploads\/2021\/11\/image-32-1024x371-1.webp\")
![\"Finding](\"https:\/\/usersearch.org\/updates\/wp-content\/uploads\/2021\/11\/image-33-1024x405-1.webp\")
![\"Follower](\"https:\/\/usersearch.org\/updates\/wp-content\/uploads\/2021\/11\/ezgif.com-gif-maker.webp\")
![\"Shared](\"https:\/\/usersearch.org\/updates\/wp-content\/uploads\/2021\/11\/image-35-1024x407-1.webp\")
10. Looking at the history of account changes<\/h2>\n\n\n\n
![\"Checking](\"https:\/\/usersearch.org\/updates\/wp-content\/uploads\/2021\/11\/image-36-1024x339-1.webp\")
![\"Wayback](\"https:\/\/usersearch.org\/updates\/wp-content\/uploads\/2021\/11\/image-37-1024x562-1.webp\")
11. Analyzing the cost of advertising in the account<\/h2>\n\n\n\n
![\"Finding](\"https:\/\/usersearch.org\/updates\/wp-content\/uploads\/2021\/11\/image-38-1024x878-1.webp\")
<\/a>12. Search for accounts with the same username in other services<\/h2>\n\n\n\n
![\"\"](\"https:\/\/usersearch.org\/updates\/wp-content\/uploads\/2021\/11\/image-40-1024x571-1.webp\")
<\/a>Summary<\/h2>\n\n\n\n
Want to find out more on user lookups & twitter intelligence?<\/h2>\n\n\n\n