Curating and Contextualizing Twitter Stories to Assist with Social

Newsgathering

Arkaitz Zubiaga (City University of New York)

Heng Ji (City University of New York)

Kevin Knight (University of Southern California)

IUI 2013 - March 21, 2013

Motivation

● Users share about news on Twitter, often complementing news media:– News break early.

– Users contribute with additional facts/info.

● Journalists are interested in gathering facts, and finding sources.

But...

Streams of tweets are overwhelming!

Trending Stories on Twitter

Newsgathering from Twitter (I)

Newsgathering from Twitter (II)

Two main shortcomings

(1) Overwhelming amounts of contents.✔ Need of curation.

(2) Lack of context.✔ Need of contextualization.

Data

● 2,593 trending topics (Feb 1-28)– Up to 1,500 tweets per TT (3.6M tweets).

● Tweets in 46 languages.– 57.8% en, 14.9% es, 7.6% pt, etc.

● Split into:– Feb 1-21: Development set.

– Feb 22-28: Test set.

Annotation

● Annotation of the 2,593 trending topics.– Newsworthy if the story was later covered by news

media (thepaperboy.com).

– Unnewsworthy otherwise.

● 358 deemed newsworthy.

Links to news media

Data processing

● Translation of tweets into English– 98.1% translated.

– 27 of 46 languages (19 of top 20).

● Ranking of trending topics.● Curation + contextualization of contents.

Ranking of trending topics

TweetGathering

TweetGathering

TweetGathering

TweetGathering

TweetGathering

TweetGathering

TweetGathering

TweetGathering

User Study

● Tested on-site by 5 journalism practitioners.– Native English speakers.

– Twitter users.

– They use Twitter for newsgathering.

● They used the tool while thinking aloud, and we interviewed them afterward.

Feedback: news discovery

● “the ranking is very helpful, the stories in the bottom of the list are mostly memes and pointless conversations”.

● “it's easy to catch the scoop, and find out whether a story is worth exploring in more detail”.

Feedback: curation

“Twitter conversations are full of spam instead of talking about the actual

news. Having a few tweets selected really helps me discover salient tweets

instead of doing it manually”

Feedback: curation

“Earliest tweet” might be the source to follow or interview.

Feedback: search

“I'd use the search engine to look for users in a specific location”

Feedback: contextualization

“It all depends on whether the story contains links to news media. When there are, I can research the news written by others”

Feedback: contextualization

“We often look into contributing users to find sources, or even witnesses that might be

reporting about the news. We rely on those as information sources, and sometimes contact

them to learn more”

Feedback: contextualization

● Hashtags:

“It is sometimes worth exploring the hashtags that are co-occurring with the story. I was really wondering why #ows appears so frequently in a story about #wellsfargo, that’s something I needed to look into more detail”.

Feedback: contextualization

● Events:

“They show what people are commenting on the story. It’s not only about the story itself. I found in a story about a political announcement that a popular event being mentioned in the tweets was resignation, this must be a strong community that wants this politician to step down”.

Feedback: contextualization

● Named entities & external descriptions:

“They may reveal where the story is happening, and so makes it easier to locate it, as well as easily identify involved people and organizations, especially when it is culturally foreign to me”.

Final remarks / Future work

● Customized stories and contents.

● Categorize news by topic.

● Identify location of users.

● Test the tool in real-time to quantify results.

Thanks!