iPhone tweeted about 1.3 times as much as Android but had 3 times the number of negative tweets
The iPhone 8 had the highest proportion of negative tweets at 56%
The OnePlus 5 received the largest percentage of positive tweets at 63%
The Samsung Galaxy S8 scored the lowest percentage of negative and positive tweets
What can Twitter teach us about smartphones? We analysed over 220,000 tweets about iPhones and Android phones, and used sentiment analysis software to find out which brand is actually winning over the masses.
For our first analysis, we collected 110,675 tweets containing “iPhone” or “Android” to calculate how people actually feel about major phone brands like Samsung, OnePlus, Pixel and Apple. Although the iPhone was tweeted about a third more than Android, proportionally it had three times the number of negative tweets – 26.7% compared to 8.4%.
We used Twitter’s search API to collect tweets posted between 27 September and 4 October 2017, in English only, containing matches for the following keywords:
Galaxy Note 8
These tweets were then analyzed using nltk.sentiment.vader – a sentiment analysis software package specifically designed for social media. This program returned a compound polarity score for each tweet between -1 and 1, where a positive result indicates an overall positive sentiment, and a negative result indicates an overall negative sentiment.
Tweets scoring 0.3 and above were considered positive, those scoring -0.3 and below were considered negative, and tweets that fell in the middle were counted as neutral. For each keyword, the number of tweets in each category was divided by the total number of tweets containing that keyword, to give the percentage of tweets about each phone/brand which expressed each sentiment.
Since Twitter does not index every single tweet for search, the figures for the number of tweets per minute were obtained via the streaming API which collects tweets in real-time. Every time a tweet occurred (in any language) mentioning either Android or iPhone, its creation time was recorded. This was run for over sixteen hours from 15:51 on 5 October to 8:06 on 6 October. The total number of tweets gathered was divided by the total number of minutes to get the average tweets per minute. This was then multiplied by the number of minutes in a day, 1440, to get the average tweets per day (rounded to the nearest thousand).
Click here for more research. For all media enquiries, please contact
Matt Mckenna Head of UK communications T: +44 20 8191 8806
Matthew Boyle is a mortgages and home services publisher at Finder. He has a 7-year history of publishing helpful guides to assist consumers in making better decisions. In his spare time, you will find him walking in the Norfolk countryside admiring the local wildlife.
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