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From Chen Li <che...@gmail.com>
Subject Re: Limitation of the current TweetParser
Date Tue, 23 Feb 2016 17:26:14 GMT
If the fields provided by twitter4j are good enough, I prefer option 1.  It
would be good to avoid a separate request to Twitter due to the overhead.

Chen

On Tue, Feb 23, 2016 at 12:13 AM, Jianfeng Jia <jianfeng.jia@gmail.com>
wrote:

> Good to know there is another request inside twitter4j.
> I think given the popularity of twitter4j, if we can parse all the fields
> in list 1 to ADM then it will be good enough.
>
> > On Feb 23, 2016, at 12:00 AM, abdullah alamoudi <bamousaa@gmail.com>
> wrote:
> >
> > Jianfeng,
> > We are using twitter4j api to get tweets as Status objects. I believe
> that
> > twitter4j itself discards the original JSON when creating Status objects.
> > They provide a method to get the full json:
> >
> > String rawJSON = DataObjectFactory.getRawJSON(status);
> >
> > This method however sends another request to Twitter to get the original
> > JSON.
> > We have a few choices:
> > 1. be okay with what twitter4j keeps {CreatedAt, Id, Text, Source,
> > isTruncated, InReplyToStatusId, InReplyToUserId, InReplyToScreenName,
> > GeoLocation, Place, isFavorited, isRetweeted, FavoriteCount, User,
> > isRetweet, RetweetedStatus, Contributors, RetweetCount, isRetweetedByMe,
> > CurrentUserRetweetId, PossiblySensitive, Lang,Scopes,
> WithheldInCountries}.
> > However this means that we will not get additional feeds in case the
> actual
> > data structure change. We can actually change this into JSON object using
> > the method above and then we can use our ADM parser to parse it.
> >
> > 2. Instead of relying on twitter4j, we should be able to get the JSON
> > objects directly using http requests to twitter. This way always gives us
> > the complete JSON object as it comes from twitter.com and we will get
> new
> > fields the moment they are added.
> >
> > I think either way should be fine and I actually think that we should
> stick
> > to twitter4j for now and still use a specialized tweet parser which will
> > simply transform the objects fields into ADM fields unless there is a
> > strong need for fields that are not covered by the list in (1).
> >
> > My 2c,
> > Abdullah.
> >
> >
> >
> > On Tue, Feb 23, 2016 at 3:46 AM, Jianfeng Jia <jianfeng.jia@gmail.com>
> > wrote:
> >
> >> Dear devs,
> >>
> >> TwitterFeedAdapter is nice, but the internal TweetParser have some
> >> limitations.
> >> 1. We only pick a few JSON field, e.g. user, geolocation, message
> field. I
> >> need the place field. Also there are also some other fields the other
> >> application may also interested in.
> >> 2. The text fields always call getNormalizedString() to filter out the
> >> non-ascii chars, which is a big loss of information. Even for the
> English
> >> txt there are emojis which are not “nomal”
> >>
> >> Apparently we can add the entire twitter structure into this parser. I’m
> >> wondering if the current one-to-one mapping between Adapter and Parser
> >> design is the best approach? The twitter data itself changes. Also there
> >> are a lot of interesting open data resources, e.g. Instagram,FaceBook,
> >> Weibo, Reddit ….  Could we have a general approach for all these data
> >> sources?
> >>
> >> I’m thinking to have some field level JSON to ADM parsers
> >> (int,double,string,binary,point,time,polygon…). Then by given the schema
> >> option through Adapter we can easily assemble the field into one record.
> >> The schema option could be a field mapping between original JSON id and
> the
> >> ADM type, e.g. { “id”:Int64, “user”: { “userid”: int64,..} }. As
such,
> we
> >> don’t have to write the specific parser for different data source.
> >>
> >> Another thoughts is to just give the JSON object as it is, and rely on
> the
> >> user’s UDF to parse the data. Again, even in this case, user can
> >> selectively override several field parsers that are different from ours.
> >>
> >> Any thoughts?
> >>
> >>
> >> Best,
> >>
> >> Jianfeng Jia
> >> PhD Candidate of Computer Science
> >> University of California, Irvine
> >>
> >>
>
>
>
> Best,
>
> Jianfeng Jia
> PhD Candidate of Computer Science
> University of California, Irvine
>
>

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