## 2 Literature Review
This study used the Standard account. There are also two methods of data acquisition: Streaming data and Archive, which contains either past or historical data [25]. Both Twitter data acquisition methods require the use of a different Twitter API, which is provided by the platform after meeting certain requirements. For Twitter streaming data acquisition, Twitter Standard API v2 is required. By requesting access through the developer portal, it is possible to get a quota of 50 tweets/15 min. With streaming data acquisition using Twitter API v2, the maximum number of data retrievals served by the Twitter database is based on a 15-min timeframe, and the request limit interval is fifteen minutes. For standard APIs, the database allows a maximum of 450 streaming data requests in 15-min intervals [1]. The procedure for collecting Twitter streaming data involves determining a specific reference point and radius [2]. The point radius number is expressed in latitude, longitude, and radius and is entered in the data collection program script. Twitter limits the data capture radius to less than 25 miles (40.2 km) [7]. Since there are two techniques for retrieving data, another question arises: whether streaming data or historical data alone are sufficient, or do both methods need to be used to provide enough data for the modeling? For the purposes of this study, archival data will be used for data modeling purposes and will be compared with the trip production model based on conventional data (house-hold surveys and roadside interviews) collected in 2018. To acquire historical data, the Twitter platform provides four types of APIs: 1. Standard API v1.1 (a free version, for the past seven days; data accuracy is not complete), 2. Premium API v1.1 (a paid version, which provides either the last 30 days of Tweets or access to Tweets from as early as 2006), 3. Enterprise (a paid version; either the last 30 days of Tweets or access to Tweets from as early as 2006 along with technical support from Twitter). 4. Academic Research for API v2 (a free version published in January 2021 for research only; access to Tweets from as early as 2006 with complete data accuracy). The acquisition of archival data for academic research at no charge is a new Twitter access facility for research only. To access data, researchers must first make an application ([[https://developer.twitter.com/en/portal/products](https://developer.twitter.com/en/portal/products)]([https://developer.twitter.com/en/portal/products](https://developer.twitter.com/en/portal/products)) (accessed on 22 September 2020)). Archived data include data since 2006. Maximum data collection is 10,000,000 per month/project. ([[https://developer.twitter.com/en/portal/projects](https://developer.twitter.com/en/portal/projects)]([https://developer.twitter.com/en/portal/projects](https://developer.twitter.com/en/portal/projects)) (accessed on 22 September 2020)). Archive data facilities were previously provided for enterprise API owners and paid for [26]. Data acquisition includes the process of gathering, filtering and cleaning the unstructured data [27]. This study has limited the process of pulling, or retrieving, data from the Twitter platform and shows the methods and results of retrieved streaming data from the Twitter database, using API Standard V2; and archive data, using API research. For streaming data retrieval, API Standard v2 was applied, which includes a filter for the location of a reference point within a certain radius, as described in the Twitter tutorial [2]. API Research was applied for archive data retrieving. This paper also discusses the performance of Twitter data streaming collection methods, such as when using single point or multi-points of reference. These two items need to be disclosed because, on one hand, appropriate and sufficient Twitter data are needed for this research. On the other hand, Twitter has also made changes in its policies and technical procedures for accessing its database [14], especially for academic projects [6].