X Organic (Twitter Organic)

X or Twitter Organic are non-paid, natural reach and engagement of tweets. It includes the interactions, retweets, likes, and mentions that happen without any promotion or advertising efforts, showcasing the genuine interest and response from the Twitter user base.

Refer to Twitter's official documentation to see all available endpoints from the Twitter API.

Authentication Methods

X Organic (Twitter Organic) supports more than one way to connect. Pick one when you create the authorizer in Dataddo:

• X Custom (formerly Twitter) - use your own app credentials (for advanced setups).
• X v1 (formerly Twitter)
• X v2 (formerly Twitter)

Authorize Connection to X (Twitter)

In X (Twitter)

To authorize your Twitter account, you will need client ID and client secret. Make sure your account is subscribed to a paid plan.

1. In your Twitter account, navigate to the Developer Portal

2. Scroll down and click on Subscribe to Basic. You can also choose Sign up for Free Account option but you won't be able to retrieve any Tweets data.

3. Write your use case for accessing the Twitter API, check all boxes, and Submit. You can use this template:

   I aim to gather insights from my Tweets' data using the API. My current focus is on extracting metrics like the number of comments, impressions, and likes. I do not intend to use this data for generating new content. While I may consider obtaining data from my other accounts in the future, it is not in the immediate plan.
   

4. In the menu on the left, click on Projects and Apps.

5. Select your newly created app, scroll down to User authentication settings, and click on Set up.

6. Configure your user authentication settings:

   1. App permissions: Make sure to check read permissions.
   2. Type of App: Select the Web App, Automated App or Bot option.
   3. App info:
      1. Callback URL/Redirect URL: Insert the Dataddo redirect URL (https://app.dataddo.com/settings/service/twitter).
      2. Website URL: Use your website URL (e.g. https://example.com/).

7. Save and copy your Client ID and Client Secret. If you lose your Client Secret, you will have to regenerate a new one.

In Dataddo

1. On the Authorizers page, click on Authorize New Service and select Twitter Custom.
2. Fill in the following fields:
   1. Client ID: Your Twitter client ID.
   2. Client Secret: Client secret to your client ID.
3. Rename your authorizer for easier identification and click on Save.
4. You will get redirected to the Twitter login page. Login with your usual Twitter credentials.

Create Twitter Organic Data Source

Creating a data source takes you through six steps, shown in the progress bar at the top of the wizard. Each step is explained below.

1. Pick the connector

On the Sources page, click Create Source, then select the connector from the catalog. Use the search bar or the category tabs if you do not see it right away. You can rename the source at any time using the pencil icon next to its name.

2. Select the dataset

A dataset defines the shape of your data: which fields you get and how they relate. Select the dataset you want; you can still fine-tune the exact fields later.

• Each dataset has a short description of what it contains. Use the search box to find a dataset, attribute, or metric by name.
• The panel on the right previews the selected dataset's fields. For each field you can see its data type, whether it holds sensitive data (personal fields such as name or email are flagged), and which other datasets it links to, so you can see how the datasets relate.

3. Choose the account

This step selects what Dataddo reads from.

• Authorizer: Select an account you have already authorized from the drop-down. If you have none yet, choose Add new account and follow the prompts. If no authorizer is selected, Dataddo asks you to authorize before you continue.
• What to extract from: Select the exact entity you want to pull data from. Depending on the service this may be labelled an account, property, profile, workspace, or similar, sometimes with a sub-level to choose as well.
• Multiple accounts: To pull the same data from every entity you can access, turn on Automatically collect data from all .... This is multi-account extraction. Leave it off to choose them by hand.

4. Refine the attributes and metrics

The dataset already sets the structure. Here you fine-tune it: tick or untick the specific attributes and metrics you want to keep, and use the search box to find a field quickly. Click Test on Sample Data at any point to preview the result before you continue.

5. Add metadata columns (optional)

Two optional columns help your destination handle the data.

• Dataddo Hash (Include Row Hash): a fingerprint built from the columns you pick. It works as a natural key, so your destination can deduplicate rows and run upserts instead of creating duplicates. Turn it on, then select the columns that uniquely identify a row.
• Dataddo Extraction Timestamp: the time each row was extracted. Use it to watermark the data, for example to build slowly changing dimensions or to track when a value last changed.

6. Set the schedule

Decide how often Dataddo runs the extraction.

• Frequency: how often the pipeline runs, for example daily. Click Show advanced settings to also set the exact hour and minute (UTC).
• Date range: the relative window each run extracts, for example "Yesterday". The window moves forward on every run.
• Historical data: a new source starts from the current window. To load older data, run a full data re-sync after the source is created.
• Allow Empty Data Extractions: when on, a run that returns no data records zero rows instead of failing. Turn it on if the source can legitimately have periods with no data.

Click Save. Your data source is ready.

Data Coverage

X Organic (Twitter Organic) exposes the following datasets. Each dataset maps to a table you can extract. Example fields are a representative sample; each dataset returns more columns.

How Data Extraction Works

None of this connector's datasets use a date range. Every run pulls all currently available data.

Metadata Columns

When you create a source, you can add these Dataddo metadata columns to the extracted data:

• dataddo_hash - a fingerprint built from each record's key fields. It works as a natural key, so it is ideal for upserts (updating existing rows in your destination instead of creating duplicates).
• dataddo_extraction_timestamp - the date and time the row was extracted. Use it to track how records change over time, for example to build slowly changing dimensions.

Troubleshooting

Data Preview Unavailable

No data preview when you click on Test Data might be caused by an issue with your source configuration. The most common causes are:

• Date range: Try a smaller date range. You can load the rest of your data afterward using manual data load.
• Insufficient permissions: Please make sure your authorized account has at least admin-level permissions.
• Invalid metrics, attributes, or breakdowns: You may not have any data for the selected metrics, attributes, or breakdowns.
• Incompatible combination of metrics, attributes, or breakdowns: Your selected combination cannot be queried together. Please refer to the service's documentation to view a full list of metrics that can be included in the same data source.

Related Articles

Now that you have successfully created a data source, see how you can connect your data to a dashboarding app or a data storage.

Sending Data to Dashboarding Apps

• Simple Data Integration to Dashboards
• Data Backfilling to Dashboarding Apps

Sending Data to Data Storages

• Batch Ingestion to Data Warehouses
• Data Backfilling to Storages

Other Resources

• Troubleshooting
• Extraction Logs
• Data Duplication