I want to extract tweets from twitter for a specific period and do a sentiment analysis, can someone help me?

% So far I can collect tweets with this code, and in the output file of the variables (tweets) I want to have a column with the date, PLEASE HELP ME!

clear;
% a sample structure array to store the credentials
creds = struct('ConsumerKey','xxx',...
    'ConsumerSecret','xxx',...
    'AccessToken','xxx',...
    'AccessTokenSecret','xxx');

% set up a Twitty object
addpath(genpath('C:\Users\Felix\Desktop\Thesis\twitter\twitter analyser\twitty')); % Twitty
addpath(genpath('C:\Users\Felix\Desktop\Thesis\twitter\twitter analyser\JSON Parser')); % Twitty's default json parser
addpath(genpath('C:\Users\Felix\Desktop\Thesis\twitter\twitter analyser\jsonlab')); % I prefer JSONlab, however.

tw = twitty(creds); % instantiate a Twitty object
tw.jsonParser = @loadjson; % specify JSONlab as json parser

% search for English tweets that mention .....
Volkswagen = tw.search('Volkswagen','count',100,'date',2015-07-01,'include_entities','true','lang','en');
Allianz = tw.search('Allianz','count',100,'date',2015-07-01,'include_entities','true','lang','en');
both = tw.search('Volkswagen Allianz','count',100,'include_entities','true','lang','en');
% load supporting data for text processing
scoreFile = 'AFINN/AFINN-111.txt';
stopwordsURL ='http://www.textfixer.com/resources/common-english-words.txt';

% process the structure array with a utility method |extract|
[VolkswagenUsers,VolkswagenTweets] = processTweets.extract(Volkswagen);
% compute the sentiment scores with |scoreSentiment|
VolkswagenTweets.Sentiment = processTweets.scoreSentiment(VolkswagenTweets, ...
    scoreFile,stopwordsURL);

% repeat the process for hachette
[AllianzUsers,AllianzTweets] = processTweets.extract(Allianz);
AllianzTweets.Sentiment = processTweets.scoreSentiment(AllianzTweets, ...
    scoreFile,stopwordsURL);

% repeat the process for tweets containing both
[bothUsers,bothTweets] = processTweets.extract(both);
bothTweets.Sentiment = processTweets.scoreSentiment(bothTweets, ...
    scoreFile,stopwordsURL);

% calculate and print NSRs
VolkswagenNSR = (sum(VolkswagenTweets.Sentiment>=0) ...
    -sum(VolkswagenTweets.Sentiment<0)) ...
    /height(VolkswagenTweets);
AllianzNSR = (sum(AllianzTweets.Sentiment>=0) ...
    -sum(AllianzTweets.Sentiment<0)) ...
    /height(AllianzTweets);
bothNSR = (sum(bothTweets.Sentiment>=0) ...
    -sum(bothTweets.Sentiment<0)) ...
    /height(bothTweets);
fprintf('Volkswagen NSR  :  %.2f\n',VolkswagenNSR)
fprintf('Allianz NSR:  %.2f\n',AllianzNSR)
fprintf('Both NSR    : %.2f\n\n',bothNSR)

% plot the sentiment histogram of two brands
binranges = min([VolkswagenTweets.Sentiment; ...
   AllianzTweets.Sentiment; ...
    bothTweets.Sentiment]): ...
    max([VolkswagenTweets.Sentiment; ...
    AllianzTweets.Sentiment; ...
    bothTweets.Sentiment]);
bincounts = [histc(VolkswagenTweets.Sentiment,binranges)...
    histc(AllianzTweets.Sentiment,binranges)...
    histc(bothTweets.Sentiment,binranges)];
figure
bar(binranges,bincounts,'hist')
legend('Volkswagen','Allianz','Both','Location','Best')
title('Sentiment Distribution of 100 Tweets')
xlabel('Sentiment Score')
ylabel('# Tweets')