Web advertising spend tops £4bn for first time

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By Ramy Ghaly

Online advertisers in the UK took their annual spend to more than £4bn for the first time last year as the digital market share hit a record high.

Research published today by the Internet Advertising Bureau (IAB) and the accountant PricewaterhouseCoopers showed that online advertising grew by 12.8 per cent, from £3.5bn in 2009 to £4.1bn a year later.

The digital share of the UK’s total advertising spend of £16.6bn last year rose to 25 per cent.

The consensus expectation for online advertising for this year is growth of 7.7 per cent, although the IAB said its internal predictions were more optimistic.

Much of 2010’s online growth was driven by display advertising, which increased by 27.5 per cent from a year earlier to £945.1m, as more and more companies shifted spending on to the web.

Search advertising continues to dominate online advertising spending in the UK, which rose 8 per cent in 2010 to £2.3bn.

By THE INDPENDENT via Ctrl-News

What are the most challenging issues in Sentiment Analysis(opinion mining)?

A Twitter tweet

Image via Wikipedia

Ramy Ghaly January 28, 2011

Hossein Said:

Opinion Mining/Sentiment Analysis is a somewhat recent subtask of Natural Language processing.Some compare it to text classification,some take a more deep stance towards it. What do you think about the most challenging issues in Sentiment Analysis(opinion mining)? Can you name a few?

Hightechrider Said:

The key challenges for sentiment analysis are:-

1) Named Entity Recognition – What is the person actually talking about, e.g. is 300 Spartans a group of Greeks or a movie?

2) Anaphora Resolution – the problem of resolving what a pronoun, or a noun phrase refers to. “We watched the movie and went to dinner; it was awful.” What does “It” refer to?

3) Parsing – What is the subject and object of the sentence, which one does the verb and/or adjective actually refer to?

4) Sarcasm – If you don’t know the author you have no idea whether ‘bad’ means bad or good.

5) Twitter – abbreviations, lack of capitals, poor spelling, poor punctuation, poor grammar, …

 

ealdent Said:

I agree with Hightechrider that those are areas where Sentiment Analysis accuracy can see improvement. I would also add that sentiment analysis tends to be done on closed-domain text for the most part. Attempts to do it on open domain text usually winds up having very bad accuracy/F1 measure/what have you or else it is pseudo-open-domain because it only looks at certain grammatical constructions. So I would say topic-sensitive sentiment analysis that can identify context and make decisions based on that is an exciting area for research (and industry products).

I’d also expand his 5th point from Twitter to other social media sites (e.g. Facebook, Youtube), where short, ungrammatical utterances are commonplace.

 

Skarab Said:

I think the answer is the language complexity, mistakes in grammar, and spelling. There is vast of ways people expresses there opinions, e.g., sarcasms could be wrongly interpreted as extremely positive sentiment.

 

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