1. Rumors identification and Mitigation
Abstract; Rumor is a piece of information that is believed to be true unless it is proven wrong. Scientifically speaking, rumor is a specific preposition of belief which is verbally transmitted to individuals without measuring its truth. Spreading rumor is both: intentional and un-intentional, especially on the social networks where the identities may well easily be unknown and flow of information is massive. This research study is focused to determine the dynamics of the rumors spreading across the social networks and the identification of the source of the rumors initiation. The study address generating graphs of the Twitter population and emphasis to identify the degree of connectivity among the individuals in the graph. The first phase of the study identifies that whether a piece of information is a rumor? The monitoring nodes are constructed and the weighted evaluation is performed that demonstrates that if the rumor is being propagated from a certain point onwards. As rumors have a broad range of classification we address “Technology Rumors” in this study. In the later part of this research, the source of rumors and rumor reduction methods are also discussed.
a. To identify a respective graph to download and store data in tabular format.
b. To identify “Monitor Nodes” in the graph.
c. To detect the source of rumor and to develop an algorithm to restrict the spreading of rumors.
d. To measure the performance of monitors by injecting the rumors.
e. To analyses the results and measure the performance.
2. Usability Analysis for DETC Applications
Abstract: Over the years some applications have been prepared by the DETC at the King Saud University. The utilization of technology is inevitable to be at par with the current developments in the academia around the world. The facilitation and academic leadership does not come only by the academic excellence but also by the use of technological advancements that have helped the world to be benefited from the electronic services.. In this project we only discuss the three of the available services namely 'Tawasal', 'Faculty Web sites' and 'New Student' applications to measure their usability. The usability analysis is being performed by following the established guidelines for this purpose. Accordingly, the positive impact of the electronic services is highlighted and analyzed for the future development.
a. To measure the usability of the applications developed by DETC
b. To develop the understanding about the un-identified functions
c. To highlight the positivity’s of the applications
d. To provide a feedback for the future versions
e. To enhance the user experience and to validate the non-functional requirements.
1. Smartphone’s Popularity Measurement
Abstract: The parameters to determine the popularity of the digital commodities and services can well be determined by the social media indices. The social media through its ‘Like’ and ‘Follow’ options has started setting the trends for the future market economy. A study was conducted to gage the popularity of the two smart phone industry leaders, namely Samsung and Apple. The study has been conducted by using the official accounts of Samsung and Apple on Twitter. Study-specific code was developed, data was collected, formulated, and analyzed by using the multi-purpose and multi-level queries. The results are classified by languages, cities, countries, and continents. To further consolidate the results, a sample of followers is selected to observe the impact by using the Klout service.
a. Samsung is universally more popular smartphone brand as compared to Apple.
b. Android is more popular OS as compared to iOS.
c. Apple’s popularity is reasonable in English speaking countries, while Samsung’s popularity is universal including English speaking countries.
d. Samsung leads Apple in five out of six livable continents.
e. Apple’s followers are more influential than Samsung followers.
f. Apple’s followers are more popular as compared to Samsung followers.
2. Maximization of Tweet’s Viewership
Abstract: Increase in Twitter’s popularity has been phenomenal over time and the Tweets now, are not only a mean of status update and one-on-one communication but widely used for the trend setting and marketing. The probability that a Tweet will be seen by the user when he was offline is very low. In order to increase the throughput of the responses it is important to determine the number of individuals online so that the Tweet is seen by maximum number of users. This research focuses on identifying the individual users from Saudi Arabia based on the parameters already set for the conduct of this study. The time stamped data for 1000 selected individuals is retrieved from Twitter and their data is analyzed accordingly. The number of online users by recording the ‘last seen’ status are observed. The retrieval of data is based on number of experiments that were run on same time in all days of the week to reduce the inconsistent patterns. The data is then analyzed to see the time slots where the online user percentage is higher as compared to other time slots. The results of the study are focused to identify and recommended the timings when the Tweets are better valued and the impact is considerable.
a. Most Followers are online on Friday followed by Monday in most cases
b. Least number of followers becomes online on Thursday followed by Wednesday.
c. Major part of social connectivity is done after the office hours.
d. The peak of social activity is gained between 10 p.m. to 2 a.m. while the slope is observed from 4 am to 2 pm, giving an impression that most of the social networking is done late night.
e. It is observed that on Thursday, least followers come online compared to other days of the week, the decreasing online trends are also observed on the Wednesday evening and night. It can be concluded that on weekend evening the individual’s better like to spend time in social gathering and travel rather than social networking.
3. Popularity Analysis for Saudi Telecom
Abstract: The aim of this study is to investigate the popularity of the telecom companies in Saudi Arabia by considering their profiles on Twitter. Telecommunication plays a vital role in making the communication possible among individuals at geographically distinct locations. With the arrival and penetration of smartphones as a standard, the job of service providers has not remained limited to provide better messaging and voice quality but has been extended to provide competitive value added service and social connectivity to grab and maintain the customer’s pool. This research study, take into consideration three leading telecom operators namely Saudi Telecom Company (STC), Mobily and Zain. The popularity of the telecom companies is evaluated by considering their following on Twitter by confirming the location details and then by executing multi-purpose queries on the verified data to yield interesting results about the popularity of the telecom operators. This study, thus identifies the most popular service provider based on the Twitter following in different regions and cities and based on the provincial data a leading telecom operator in Kingdom of Saudi Arabia is also identified.
a. Riyadh hosts 44% of STC, 39% of Mobily and 37% of Zain’s total followers.
b. 64% followers of Mobily, Zain and STC live in Jeddah and Riyadh.
c. More than 75% of the followers for Mobily, Zain and STC, live in four major cities (Riyadh, Jeddah, Makkah and Dammam)
d. STC is a leading trust bearer for expatriates
e. STC outnumbers Mobily in popularity, in 12 out of 13 provinces in KSA except Madina.
f. STC is more popular than Zain and Mobily in all cities except Makkah.
g. STC is more popular than Mobily and Zain in KSA. STC’s followers are more popular and influential as compared to Zain and Mobily.
4. Students’ Academic Performance and Social Media
Abstract: Social networks have evolved as major source of information sharing and fun and social networks encourage the extensive usage due to the nature of the diversified interests for the individuals, specially the teen-agers. The teenagers are also required to put ample time/ effort in their studies to perform better academically. As a general perception, it has been noted that the student’s grades are affected by the over-usage of the social media. This project works to identify the impact of excessive usage of social media on the student’s grades.
a. To determine a reasonable sample size to conduct the study
b. To retrieve the quantitative information and verify them from the social networks by analyzing their profiles
c. To identify the social networking patterns of the university students
d. To observe the academic grading of the students w.r.t the social networking usage
e. To analyses and report the impact of excessive social networking usage.
5. Impact of Weekend Change in Social Culture
Abstract: Increase in Twitter’s popularity has been phenomenal over time and the Tweets now, are not only a mean of status update and one-on-one communication but widely used for the trend setting and marketing. The probability that a Tweet will be seen by the user when he was offline is very low. In order to increase the throughput of the responses it is important to determine the number of individuals online so that the Tweet is seen by maximum number of users. This research focuses on identifying the individual users from Saudi Arabia and Gulf region (having the same time zone) based on the parameters already set for the conduct of this study. The time stamped data for selected individuals is retrieved from Twitter and their data is analyzed accordingly. The number of online
Users by recording the ‘last seen’ status are observed. The retrieval of data is based on number of experiments that were run on same time in all days of the week to reduce the inconsistent patterns. The data is then analyzed to see the time slots where the online user percentage is higher as compared to other time slots. Some results were recorded few months back when Thursday and Friday were the weakened days. The experiments will be re-run now (when the weakened has changed to Friday and Saturday) and the changes in the social behavior are recorded and analyzed.
a. To select number of Twitter users who have massive following, as required to accomplish the experiments and to conduct extensive experimentation to identify the number of online followers for each user that we use in experiments.
b. To identify the social networking trends and peak/off hours.
c. To demonstrate the weekly trends by focusing on the peak / steep days.
d. To prepare customized recommendation (Time to Tweet) for the customers, willing to market their brands.
e. To identify and analyse the change in the social networking trends due to change in the weekend days (i.e. from Thursday-Friday to Friday-Saturday).