Academics should receive increased access (beyond seven days) to historical data. The seven-day limitation severely limits academic inquiry and is a primary driver behind extravagant costs for those using Twitter data in their research.

Academics should not be burdened with the same rate limits as those who access the APIs for commercial means. Lifting these rate limits would significantly increase the rate at which data could be gathered, creating cost and time efficiencies for those using Twitter data in their research.

I request the Twitter to allow access to all the replies of a tweet (all the conversations of a thread). It would be very useful for academics working in user behavior analysis, argumentation mining, hate speech detection because comment or reply reflects the actual thought process of a replying user.

In the current search API, the only form of engagement for which scholars currently get accurate metadata is RTs. There is no metadata field for Replies and the field for Likes does not return the number of times a tweet has been liked by other users. This information would be very valuable for academics, especially considering that the use of the "Like" button by users has increased substantially.

I'd like access to predefined datasets that provide ideas for my research and make it easy to get started.

Take part in Social Science One (https://socialscience.one/ ) and/or work with other non-profit intermediaries such as academic libraries and data providers (for example GESIS in Germany) for Firehose access or access to the complete follow network or other large scale data. They have the most experience when it comes to researchers' needs and can act as a trustworthy partner when it comes to protecting user privacy and the like.

Many common research use-cases would be greatly facilitated by an API that could return summary level information. For instance, for any subset of tweets based on a particular query term(s) and period:

• hourly/daily/weekly counts of matching tweets




• histogram data of top hashtags / handles referenced / links shared




• proportion of retweets / replies / first posts




• proportion of dataset generated by top n contributors

These would be very valuable from a purely research perspective, but presumably they present considerable challenges for implementation. But a methodology similar to Google Trends might be possible.

Deploy a new API call to retrieve a random tweet from the index. Would be an important asset for characterization studies.

Access data about ads, reach, accounts promoted by, engagements.

Streaming was a VERY good+easy way to get low key sampling data, without digging into heavy duty "last x million tweets" data dumps. A couple of lines of code (ie minimum wasted researcher time) and you could start collecting/analysing data.

It is very much missed.

Not to mention, of course, the damage removing streaming has done to the general Twitter ecosystem: http://apps-of-a-feather.com/

Doing research in europe is becoming harder, and GDPR add some difficult on exploiting data. I would like to know if data that we can get with the Stream API can be Anonymized.

Bot-based research is an important frontier in several different academic fields, but post requests are often censored or accounts associated with such posts are often suspended-- even if they do not seem to violate Twitter's automated account policies. Perhaps there could be a mechanism where academics could petition twitter not to censor bots that are being used for academic research (assuming, very importantly, that they have been carefully vetted by IRB and/or ethics officers within Twitter)?

I'd like to directly access Twitter data without needing to write code to collect data from the API.