Twitter Webcrawler (Tool)
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| Twitter Webcrawler (Tool) | |
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| Copyright © 2016 edegan.com. All Rights Reserved. | |
Contents
Description
Notes: The Twitter Webcrawler, in its alpha version, is an expedition project involving the Twittwer API in search of a sustainable and scale-able way to excavate retweet-retweeter, favorited-favoriter following-follower relationships in the entrepreneurship Tweet-o-sphere. On the same beat, we also seek to document tweeting activities/timelines of important twitters in the same Tweet-o-sphere.
Input: Twitter database
Output: Local database documenting important timelines and relationships in the entrepreneurship Tweet-o-sphere.
Development Notes
7/11: Project start
- Dan wanted:
- First-take on Twitter API Overview
- Cumbersome API that is not directly accessible/requires great deal of configuration if one chooses to leverage e.g.
import requestslibrary.- Turns out Twitter has a long controversial history wrt third-party development. There is no clean canonical interface to access its database.
- DO NOT attempt to access Twitter API through canonical documented methods - huge waste of time
- Obsolete authentication process documented - do not be use canonical documentation for Oauth procedure
- Cumbersome API that is not directly accessible/requires great deal of configuration if one chooses to leverage e.g.
- Instead, DO USE third-party developed python interfaces such as python-twitter by bear - highly recommended in hindsight
- Follow python-twitter's documented methods for authentication
- The twitter account that I am using is
shortname: BIPPMcNairandpassword: amount- One can obtain the consumer key, consumer secret, access key and access secret through accessing the dev portal using the account and tapping
TOOLS > Manage Your Appsin the footer bar of the portal.
- One can obtain the consumer key, consumer secret, access key and access secret through accessing the dev portal using the account and tapping
- There is no direct access to Twitter database through http://, as before, so expect to do all processing in a py dev environment.
7/12: Grasping API
- The python-twitter library is extremely intricate and well-synchronized
- All queries are to be launched through a
twitter.api.Apiobject, which is produced by the authentication process implemented yesterday
- All queries are to be launched through a
>>> import twitter
>>> api = twitter.Api(consumer_key='consumer_key',
consumer_secret='consumer_secret',
access_token_key='access_token',
access_token_secret='access_token_secret')
- Some potentially very useful query methods are:
Api.GetUserTimeline(user_id=None, screen_name=None)which returns up to 200 recent tweets of input user. Really nice that twitter database operates on something as simple asscreen_name, which is @shortname that is v public and familiar.Api.GetRetweeters(status_id=None)andApi.GetRetweets(status_id=None)which identifies a tweet as a status by its status_id and spits out all the retweets that this particular tweet has undergone.Api.GetFavorites(user_id=None)which seems to satisfy our need for tracking favorited tweetsApi.GetFollowers(user_id=None, screen_name=None)andApi.GetFollowerIDs(user_id=None, screen_name=None)which seems to be a good relationship mapping mechanism for esp. the mothernodes tweeters we care about.
- Some potentially very useful query methods are:
- After retrieving data objects using these query methods, we can understand and process them using instructions from Twitter-python Models Source Code
- To note that tweets are expressed as
Statusobjects- It holds useful parameters such as
'text','created_at','user', etc - They can be retrieved by classical object expressions such as
Status.created_at
- It holds useful parameters such as
- To note that users are expressed as
Userobjects - Best part? All these objects inherit .Api methods such as AsJsonString(self) and AsDict(self) so that we can read and write them as JSON or DICT objects in the py environment
- To note that tweets are expressed as
- After retrieving data objects using these query methods, we can understand and process them using instructions from Twitter-python Models Source Code
7/13: Full Dev
Documented in-file, as below:
Twitter Webcrawler
- Summary: Rudimentary (and slightly generalized) webcrawler that queries twitter database with using twitter API. At current stage of development/discussion, user shortname (in twitter, @shortname) is used as the query key, and this script publishes 200 recent tweets of said user in a tab delimited, UTF-8 document, along with the details and social interactions each tweet possesses
- Input: Twitter database, Shortname string of queried user (@shortname)
- Output: Local database of queried user's 200 recent tweets, described by the keys "Content", "User", "Created at", "Hashtags", "User Mentions", "Retweet Count", "Retweeted By", "Favorite Count", "Favorited By".
- Version: 1.0 Alpha
- Development environment specs: Twitter API, JSON library, twitter-python library, pandas library, Py 2.7, ActiveState Komodo IDE 9.3
Pseudo-code
- function I: main driver
- generate empty table for subsequent building with apt columns
- iterate through each status object in the obtained data, and fill up the table rows as apt, one row per event
- and the main processing task being: write table to output file
- function II: empty table generator
- modular caus of my unfamiliarity with pandas.DataFrame; modularity enables testing
- function IV: authenticator + twitter API access interface setup
- authenticate using our granted consumer keys and access tokens
- obtains working twitter API object, post-authentication
- function V: subquery #1
- iterate through main query object in order to further query for retweeters, i.e. GetRetweeter() and ???
- function VI: raw data acquisitior
- grabs raw data of recent tweets using master_working_api object
- make it json so we can access and manipulate it easily
Notes:
- Modular development and unit testing are integral to writing fast, working code. no joke
- Problems with GetFavorites() method as it only returns the favorited list wrt authenticated use (i.e. BIPPMcNair), not input target user.
- Query rate limit hit while using subqueries to find the retweeters of every given tweet. Need to mitigate this problem somehow if we were to scale.
- A tweet looks like this in json:
7/14: Alpha dev wrap-up
- Black box can be pretty much sealed after a round of debugging
- All output rqts fulfilled except for output "retweeter" list per tweet
- Code is live
- Sample output is live
- Awaiting more discussion, modifications
- Ed mentioned populating a database according to Past Tweet-o-sphere experimentation/excavation results
7/15: Application on Todd's Hub Project
Notes and PC for the Todd's hub data
- Input: csv of twitter @shortnames
- Output: A main datasheet tagging each @shortname to the following keys: # of followers, # of following, # of tweets made in the past month; a side datasheet for each @shortname detailing the time signature, text, retweet count and other details of each tweet made by given @shortname in the past month.
- Summary: need to fix up auto .csv writing methods, parameters to query timeline by time signature (UPDATE: NOT POSSIBLE, LET'S JUST DO 200 RESULTS), instead of # of searched tweets.
- Pseudo-code
- We need a driver function to write the main datasheet, as well as iterate through the input list of @shortname and run alpha scrapper on each iteration.
- doesn't need to have a read.csv side function - no room for failure, no need to test
- Make ***one query*** per iteration, please.
