 similar way to the sophisticated marketing segmentation tools created by Facebook and Google.
In the final days of campaigning before the General Election, the frequency and urgency of political ads appearing on Facebook hit a new high, as reported by Who Targets Me, an independent project created to shed light on political parties’ use of Facebook advertising. When WTM passed their crowdsourced social media feeds from over 10,000 Facebook users to the Bureau of Investigative Journalism, they found that all three of the major parties were using ‘dark ads’ – ads containing material that doesn’t appear anywhere on their official party pages.
Combine this with the Labour party’s surge in popularity just before polling day, which they likely owed in no small part to social media advertising targeting young voters, and a picture starts to emerge. As reported in the Guardian, Labour’s analytics platform, Promote, is said to have merged information from Facebook with their own voter data to send highly targeted local messages. According to a campaign source, “People were seeing stories about their school and hospital, not just national messaging like the Tories were doing. It has played in to the fact that people felt Labour’s message was authentic and speaking to them and their lives” (Guardian.com).
With such findings evident, the laws as set out by the ICO seem to be a little out of date. Presumably, all of this research and social media data mining is done behind the scenes without voters’ knowledge, and as such, cannot realistically be called ‘communications’. It’s hard to say how this kind of big data use fits into the ICO’s guidance if voters are completely unaware that their personal data is being used in the first place.
The ICO seem to agree, as they launched an official investigation into the use of data analytics in political campaigning earlier this year, stressing the importance of “greater and genuine transparency about the use of such techniques to ensure that people have control over their own data and the law is upheld,” (ICO Commissioner Elizabeth Denham, bt.com).
It could be that the technology used to disseminate information has simply advanced faster than the legislation governing it, and future laws will need to take into account the grey area that is big data.
How big data disturbed US politics
As reported, the ICO came to the decision to look into political data analysis after assessing the risks to data protection posed by the alleged involvement of data-driven campaigning experts Cambridge Analytica (CA) in the EU referendum.
Cambridge Analytica specialise in detailed psychographic profiling of both voters and consumers that can be used to predict how they may behave, something the company put to good use for Donald Trump during his presidential campaign. CA created groups of similar-minded voters based on the results from over a million personality tests, taken by normal Americans online, over the phone and while out and about, scaling these up to produce an astonishingly accurate picture of the electorate at large. By combining these results with up to 5,000 data points on record about every adult in the country (data that’s available to purchase), CA was able to predict voting behaviour based on personality to an incredible degree. But whereas Trump’s campaigners were free to use data in this way on their side of the pond, the legislation governing data use in politics for UK parties make this kind of activity unlawful.
Elizabeth Denham, information commissioner at the ICO, said she believed that CA was strongly connected to those behind the Leave campaign during the run up to the Brexit decision in 2016, although CA themselves deny playing any part, paid or otherwise. Any role they may have played would have had to have been reported to the Electoral Commission, the independent body charged with overseeing elections and regulating political finance.
While the ICO’s investigation will look at the use of big data in political campaigning in general, they have made clear this will involve “deepening […] current activity to explore practices deployed during the UK’s EU referendum campaign,” (ICO Commissioner Elizabeth Denham, bt.com).
Until we have an outcome to the investigation, it remains to be seen if, and to what extent, campaigning for the EU referendum breached data protection and privacy laws. However, what is clear is the ambiguity surrounding big data use in politics, which is only made murkier by the vastly different laws in effect in different parts of the world.
What about GDPR?
In her key Brexit speech in January 2017, Prime Minister Theresa May set out her intentions for carrying the UK into a future outside of the European Union. In it she confirmed the conversion of existing EU laws into UK law, including the EU’s GDPR regulation, set to come into effect in 2018.
Secretary of State, Karen Bradley MP, has also stated,.”
It’s therefore fair to say that the government is thoroughly on board with GDPR and the toughening up of UK data protection and privacy laws that it represents. As such, their own potential forays in big data mining can be seen as all the more disturbing, given that they could be violating the very laws they claim to stand for.
Once it’s introduced, GDPR could have the power to outlaw the kind of big data voter profiling that political campaigners are likely carrying out. GDPR’s main objective is to make sure organisations can only use our personal information for the exact purpose for which it was given, so if we don’t want our data used to predict our voting behaviour by campaigners, in theory we should be able to prevent it.
How this will work in practice remains to be seen, but more stringent laws on the use of big data could mean that future UK election campaigns are carried out very differently to what we’re currently used to.Snapchat logo displayed on a phone screen is seen with a laptop in the background in this illustration photo taken in Krakow, Poland on August 10, 2022.
also slid 4.7% and 2.6%, respectively.
– The transportation company is trading up 4.3% after it reported third-quarter results, posting beats on top and bottom lines. CSX reported 52 cents in adjusted earnings per share on revenue of $3.90 billion. Analysts predicted per-share earnings of 49 cents on revenue of $3.74 billion, according to Refinitiv.
– Shares are down 7.7% following its earnings report. The employment agency missed expectations on top and bottom lines, posting per-share earnings of $1.53 on revenue of $1.83 billion. Analysts anticipated per-share earnings of $1.62 on revenue of $1.92 billion, according to StreetAccount.
– Shares shed 4.8% after the company said after the bell its third-quarter net sales declined and its bottom line was hurt by short-term headwinds. The company missed expectations on the top and bottom lines, posting $4.49 in adjusted earnings per share on revenue of $4.78 billion.
– The bank's shares dropped 12.5% after it posted third-quarter earnings that beat expectations. SVB posted per-share earnings of $7.21, compared to analysts' expectations of $7.09 per share. "We continue to see strength and momentum in our underlying business, despite persistent market challenges affecting liquidity flows to private companies, rising rates and fear of recession," said Greg Becker, president and CEO of SVB Financial Group.
– Shares slid 14% after the company reported its quarterly results. Adjusted per-share earnings came in at $1.44, compared to analysts' expectations of $1.24, according to Refinitiv. Revenues were in line with estimates at $4.81 billion. The company dialed back its fourth-quarter guidance for per-share earnings and revenue. Tenet also announced a $1 billion share buyback program.<issue_start><issue_comment>Title: [WIP] LSP: Track active requests to the language server on the client object
username_0: This is still a WIP but I wanted to get some feedback on it before I spent time cleaning it up and adding/fixing tests. It's also my first major contribution to neovim, so be kind :) (I'm not as familiar with the coding practices and guidelines that should be followed).

This PR addresses the last remaining items keeping me from switching to the native LSP client over coc.nvim. That is:

1. A way to see the currently pending (active) requests to the language server (like in a status line)
2. A way to see requests for which cancellations have been requested
3. A way to cancel pending requests on CursorMoved events that does not require wrapping all of the requests (and handlers!) in a special function.

I know that `lsp.buf_request()` already returns a list of request IDs and a function to cancel them all. This PR doesn't break any existing code that uses this. However, this particular method only works if each request is wrapped appropriately. The built-in request convenience functions don't return the result of `buf_request()` so they have to be re-written with the proper method name and location params.

Even if the request functions were rewritten to return the IDs and cancellation function, there is still no way to watch pending requests if they are cancelled by the language server (either due to a user request, or due to a ContentModified error). The RPC layer swallows these responses up and never even gives the opportunity for an observer to see that a request is no longer pending to be able to clear out any external mechanism for tracking them.

As for the design here, this was simply my first take at it. I'm sure there are better ways to do things or alternative ideas to achieve my goals above, but I'd at least like to get the