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Impact of Electronic Media, Print Media and Interpersonal Communication on Voters' Decision Making in Punjab Pakistan.

Byline: Muhammad Shabbir Sarwar and Shahzad Ali

Introduction and background

Democracy, media and elections are strongly interlinked in a modern era democracy. The democracy sans free and fair election is impossible; likewise, the free and fair election sans free media is inconceivable. Therefore, democracy is heavily dependent on elections and media in a modern democratic society (Yaser, Mahsud and Paracha, 2010).

Since the year 2002 there is a mushroom growth of electronic media in Pakistan (Bangash, 2013), which ultimately ensured an increased role of media in the General Elections (GE) 2008 and GE 2013. For the first time electronic media was used at a large scale during GE 2013 campaign by the political parties and candidates and their supporters, who progressively used electronic media advertisements as a source for reaching out to their potential voters (Saleem, Hanan and Tariq, 2015).

Although media played its role during GE 2008, however, its improved role during the GE 2013 to provide information and guidance to the voters was highlighted and praised at many forums. In their study, Saleem, Hanan and Tariq (2015) found, for the first time that electronic media was used at large scale during the GE 2013 campaigns in Pakistan by the political parties, who progressively used TV media advertisements for reaching out to their potential voters. Also, the chief election commissioner himself praised the role of media soon after the conclusion of the polling process saying that the media helped increase voters' turnout in the election (BBC, 2013).

The Punjab province has an active media landscape with printing press setup in Lahore, Islamabad, Faisalabad, Multan and large circulation of newspaper estimated at more than four million (APNS, 2013). In total 4813 daily, weekly and monthly newspapers are being published in Punjab including 2881 from Lahore, 528 from Multan, 441 from Faisalabad, 323 from Gujranwala, 276 from Bahawalpur, 170 from DG Khan, 144 from Rawalpindi and 150 from Sargodha. (DGPR, 2003 as cited in Ali 2011).

The TV penetration is around 77 percent and social media consumers are 17.4 percent having internet access. Historically in election the traditional media of drum beating, pamphlets, posters and banners are also used excessively in Punjab. Radio access to urban areas household is 24 % while in rural area it is 19% in Punjab (BBC Pakistan, 2008)

There are traditional multiple factors affecting the voters of Punjab during general elections including personal interest, locality interest, Bradarism (based on clan/caste), according to Ahmed (2006), while religious sectarianism, political affiliation, law and order situation are some other factors.

During the elections there is very common and popular notion that rich candidates who would support voters (when required) while dealing with policemen and court system, they are considered as electable, while educated and honest candidates who are not rich and have less or no strong linkages in police stations and courts, are considered non-favourite candidates (Daily Times, May 2013).

Adding to the interpersonal research and voting patterns in cities and villages, Yaser, Mahsud and Paracha (2010) observed that the rural and urban voters were influenced by the interpersonal communication differently because of variation in their exposure to the mass media. In their study on General Election 2008 conducted in Lahore, Punjab, found high level impact of IPC. While impact on city areas voters of comparative higher age, remained very low in case of IPC. They observed that TV impacted the voters more as compared to the interpersonal communication sources. However, impact of interpersonal communication remained more when compared to the radio and newspapers in their study.

2.1. Theoretical Framework and Research Questions

Media effect studies have a long history, especially when the impact is on elections and individual voting behaviors it becomes even more interesting and appealing for the researchers and democratic societies. Therefore, a lot of works has been done by media researchers and political scientists and both consider significant direct and indirect relationship in this regard.

On the basis of the literature review this study takes light from following theories:

i) The Social Relationship Theory

ii) The Two-Step Flow of Communication

2.2. Research Question

RQ: Which channel of communication among Electronic Media, Print Media and IPC impacted voters' decision the most in General Elections 2013 in Punjab, Pakistan?

2.3. Hypotheses

H: Interpersonal communication significantly impacted voters' decisions in GE 2013in Punjab, Pakistan.

3. METHOD

This research "Impact of Communication Channels on Voting Behaviours in Punjab, Pakistan: A Longitudinal Study of General Election 2013" was a panel study with data collection at two-time periods (Time 1 was one-two months before General Election 2013 and Time 2 was one-two months after GE 2013).

Quantitative research method was used to conduct this study and the data was collected through survey. Using two purpose-built questionnaires the research data was collected in two-time periods i.e. before and after General Election 2013 within a four-month time period. The researcher personally visited many districts of Punjab and also hired services of some surveyors for collecting data. These surveyors were properly guided in a training session to address all possible issues in order to ensure accuracy of the data.

3.1. Population and Sampling

This study focused on Pakistan's population wise largest province namely Punjab Province. The Election Commission of Pakistan had registered 4,99,27,112 voters in General Election 2013 (57% of Pakistan's total votes) in the province out of which 28,064,284 (56.21%) were male and 21,862,830 (43.78%) were female (ECP, 2013).

There were 10 divisions in Punjab province in 2013 and the registered voters of these all divisions were included in the survey for data collection.

Multistage Cluster Sampling technique was used to gather data sample from the research population. As reflected by the name Multistage Cluster Sampling is a kind of sampling technique which referred to the plan in which sampling process is done in different stages (Mujama, 2014).

Out of a total 36 districts of Punjab, 18 districts representing all 10 divisions of the province have been taken for this study with the sample scattered in Northern, Central and Southern Punjab. The 18 districts were selected on the basis of number of national assembly constituencies and number of registered voters.

3.2. Measurement

Data was measured while applying mixed method comprising Pearson's Regression Analysis Model, which was selected on the basis of the literature review. While, Chi-square Test, McNaymar Test, simple frequencies analysis based on percentage, Covariance during pre-and post-election panel analysis were also applied on the data to test hypotheses. Voting behaviour was the dependent variable in this study while independent variable in the study were included Interpersonal Communication, Electronic Media and Print Media and Entertainment Media.

The key variables in this study were measured by a questionnaire using self-report and surveyor-report options for educated and uneducated respondents respectively. The first part of the instrument included 10 demographic characteristics respondents i.e. age, gender, education, income, profession, religion, area (rural or urban), district, NA constituency and PP constituency.

The second part of the questionnaire measure the five variables in the research hypotheses with the help of 42 questions ordinal data, Likert Scale 1-5.

This study has mostly relied on factor analysis for assessing associations and patterns amongst the variables in order to get reliable and generalizable results and also to circumvent any validity threat. Factor analysis is a statistical method used to discover patterns in the relationships amongst variables and to reduce the number of variables by obtaining factors by combining number of variables. Principal component analysis (PCA) is the most commonly used factor extracting method which is used to replace a large set of variables by a smaller set of variables, accurately representing the larger set.

Factor Analysis Model

###Components

###Inter personnal Electronic Outdoor Print###Political

###Items###Communication###Media###Media###Media###Advertisement

###Your vote decision was influenced by friend's

###1 conversion,arguments and their wishes###0.807###0.229###0.181###0.15###-0.011

###Your vote decision was influenced by neighbour's

###2 conversation,arguments and their wishes###0.802###0.193###0.221###0.089###0.119

###Your vote decision was influenced by candidates

###3 and workers conversion,arguments and their wishes###0.759###0.157###0.201###0.051###0.198

###Your vote decision was influenced by relatives

###4 conversion, arguments and their wishes###0.756###0.255###0.116###0.151###-0.007

###Your vote decision was influenced by public

###5 processions of candidates.###0.707###0.119###0.233###0.004###0.34

###Your vote decision was influenced by mobile phone

###6 SMS of party leaders and candidates.###0.477###0.074###0.393###0.039###0.443

###7 Do you watch TV current affair Programmes?###0.205###0.778###0.033###0.119###0.122

###8 How often do you listen radio?###0.086###0.757###0.181###0.197###0.097

###9 How often do you watch TV news channels?###0.247###0.755###0.034###0.105###0.116

###Your vote decision was influenced by the debate on

###10 your favourite social media website?###0.229###0.574###0.23###0.212###0.229

###11 How often do you use Internet?###0.024###0.569###0.267###0.269###0.022

###Favourite TV current affairs programmes was

###12 influenced your vote decision?###0.228###0.565###0.141###0.275###0.483

###Favourite Radio current affairs programmes was

###13 influenced your vote decision###0.128###0.524###0.104###-0.053###-0.035

###Your vote decision was influenced by banners and

###14 posters of candidates.###0.18###0.144###0.839###0.097###0.171

###Your vote decision was influenced by pamphlets

###15 based on political party/candidate agenda/manfesto.###0.266###0.206###0.802###0.042###0.066

###Your vote decision was influenced by hoarding

###16 boards of political parties/candidates.###0.23###0.215###0.795###0.105###0.046

###Your vote decision was influenced by

###17 advertisements on vehicles.###0.189###0.124###0.761###0.081###0.271

###18 Newspaper influenced your vote decision###0.083###0.096###-0.005###0.802###0.321

###19 Favourite megazine affected your vote decision###0.233###0.074###-0.039###0.752###0.275

###20 How often do you read newspaper?###0.016###0.158###0.225###0.745###-0.107

###21 How often do you read Magazine###0.061###0.343###0.099###0.698###-0.206

###Political parties'TV advertisements affected your

###22 vote decision###0.128###0.342###0.262###0.227###0.665

###Your vote decision influenced by Phone cell or

###23 voice call of party leaders or candidates###0.351###0.062###0.401###-0.063###0.585

Items related in the previous literature were used: for example, general questions like "How often do you watch TV news channels." Do you read newspaper? Do you use Internet? Do you read magazine? Favourite TV channels would affect your vote decision. Favourite Newspaper reading would affect your vote decision." Giving representation to all sort of communication channels questions form all sections were included. Five factors with significant value emerged in the factor analysis and the same were named as "Interpersonal Communication", "Electronic Media", "Outdoor Media", "Print Media" and "Political Advertisements".

Last factor "Political Advertisements" comprised only two queries which were significantly varied from the all 23 items during the factor analysis. These items included: "Political parties TV advertisement would affect your vote decision" and "Your vote decision will be influenced by phone calls or voice calls of party leaders and workers." A total 23 items are described in Table 3.6.

The Scree Plot reflects around five factors are significant while other show insignificant difference, hence they all have been excluded from the study.

3.5.1. Reliability

The coefficients which are largely used to check reliability have a range from 0.00 to 1.00, while lower coefficient indicates lower reliability and higher coefficients suggest greater level of reliability (Kimberlin and Winterstein, 2008).

Cronbach's Alpha measure is vastly used in social sciences studies to check the reliability. The value of alpha coefficient >0.7 is considered fair reliability in social sciences studies.

Table 3. 1. Reliability Test for all the factors

###Cronbach's###Number

###Sr. No.###Variables###Alpha###of Items

###Interpersonal###0.863###6

###1###Communication

###2###ElectronicMedia###0.792###7

###3###Outdoor Media###0.898###4

###4###Print Media###0.789###4

###5###Political Advertisement###0.483###2

All five factor's Reliability Test was conducted and found that all factors were good at the test except last factor Political Advertisement, which was slightly unsatisfactory, as the Cronbach's Alpha value was <0.7. This factor was ignored and was not considered for further analysis for the study. Removing this factor did not affect the study results because this was neither part of research questions nor hypotheses. After the positive satisfactory value of the reliability test of the first four factor, the factor items were computer average (mean) into single variables. Hence, 23 items were transformed into five new variables titled: Interpersonal Communication (IPC), Electronic Media (EM), Outdoor Media (ODM), Print Media (PM) and Pol. Ads (PA).

4.1. Factor Analysis

Comparative Impact of Interpersonal Communication (IPC), Electronic Media (EM), Outdoor Media (OM) and Print Media (PM) on voting behaviour

Table 4.1 Paired Samples Statistics

###Mean###N###Std. Deviation###Std. Error Mean

###IPC_Mean T1###2.8739###1684###1.00992###.02461

Pair 1

###IPC_Mean_T2###2.7921###1684###1.03177###.02514

###EM_Mean###2.6966###1697###.90873###.02206

Pair 2

###EM_Mean_T2###2.8339###1697###.63700###.01546

###OM_Mean###2.6277###1673###1.11900###.02736

Pair 3

###OM_Mean_T2###2.6326###1673###1.14152###.02791

###PM_Mean###2.1208###1569###.99465###.02511

Pair 4

###PM_Mean_T2###2.5573###1569###.84603###.02136

Table 4.2 Paired Samples Test

###Paired Differences###t###df###Sig. (2-

###tailed)

###Mean###Std.###Std. Error###95% Confidence

###Devia###Mean###Interval of the

###tion###Difference

###Lower###Upper

###IPC_Mean T1 -

Pair 1###IPC_Mean_###.08180###.8514 .02075###.04111###.12249###3.94###1683###.000

###T2

###EM_Mean T1 -

Pair 2###EM_Mean###-.13731###1.249 .03034###-.19681###-.07781###-4.53###1696###.000

###T2

###OM_Mean T1

Pair 3###- OM_Mean###-.00493###.9455 .02312###-.05027###.04041###-.21###1672###.831

###T2

###PM_Mean T1 -

###-

Pair 4###PM_Mean###-.43653###1.037 .02617###-.48786###-.38520###1568###.000

###16.68

###T2

A paired-samples t-test was conducted to evaluate the impact difference of IPC, EM, OM and PM through Time I and Time2. There was a statistically significant decrease in IPC scores from Time 1 (M =2.8739, SD = 1.00) to Time 2 (M = 2.792, SD =1.03), t (1683) = 3.94, p <. 0005 (two-tailed). On the other hand, influence of Electronic Media from Time 1 (M = 2.697, SD = .91) to Time 2 (M = 2.834, SD = .064), t (1697) = -4.53, p <.0005 (two-tailed) and influence of Print Media from Time 1 (M =2.12, SD = 0.025) to Time 2 (M = 2.56, SD = 0.021), t (1568) = -16.68, p . 05 (two-tailed).

4.2. Logistic Regression

Table 4.3 Omnibus Tests of Model Coefficients

###Chi-square###df###Sig.

###Step###151.598###4###.000

###Step 1###Block###151.598###4###.000

###Model###151.598###4###.000

Table 4.4 Model Summary

Step###-2 Log likelihood###Cox and Snell R Square###Nagelkerke R Square

1###1975.956a###.094###.125

Table 4. 5 Hosmer and Lemeshow Test

Step###Chi-square###Df###Sig.

1###27.636###8###.001

Table 4.6 Variables in the Equation

###B###S.E.###Wald###df###Sig.###Exp(B)###95% C.I.for EXP(B)

###Lower###Upper

###IPC_Mean###.656###.068###94.183###1###.000###1.927###1.688###2.200

###EM_Mean###.011###.077###.021###1###.885###1.011###.870###1.176

Step 1a###OM_Mean###-.105###.061###2.997###1###.083###.900###.799###1.014

###PM_Mean###-.412###.067###37.465###1###.000###.662###.580###.756

###Constant###-.747###.197###14.348###1###.000###.474

Direct Logistic Regression was performed to assess the impact of a number of factors on the likelihood that respondents would report that they had voted. The model contained four independent variables (Interpersonal communication, Electronic Media, Outdoor Media and Print Media). The full model containing all predictors was statistically significant, I2 (4, N = 1535) = 151.598, p < .0005, indicating that the model was able to distinguish between respondents who voted and those whodidn't. The model as a whole explained between 9.4% (Cox and Snell R square) and 12.5% (Nagelkerke R squared) of the variance in vote casting status, and correctly classified 64.6% of cases.

As depicted in the results, only two of the independent variables made a unique statistically significant contribution to the model (Interpersonal Communication and Print Media) The strongest impact of a predictor on predicted variable casting vote was interpersonal communication, recording an odds ratio of 1.93. This indicated that respondents who had casted vote they were almost 2 times more likely to influenced by the increasing effect of Interpersonal communication. Similarly, print media has an effect of 0.662 odd ratio with negative Beta value, which indicated that vote casting was likely to decrease by the effect of print media. Meanwhile, other independent variable did not have any significant impact in Time 1.

Table 4. 7 Impact of communication channels on voting behavior with ref. to Age groups (Variables in the Equationa

Age###B###S.E.###Wald###df###Sig.###Exp(B)

###EM_Mean_T 2###-.144###.207###.482###1###.487###.866

###IPC_Mean_T 2###.391###.132###8.735###1###.003###1.479

18-21year###Step 1b###OM_Mean_T 2###.030###.121###.059###1###.807###1.030

###PM_Mean_T 2###-.391###.151###6.690###1###.010###.677

###Constant###.895###.768###1.358###1###.244###2.448

###EM_Mean_T 2###-.328###.206###2.535###1###.111###.720

###IPC_Mean_T 2###.800###.129###38.250###1###.000###2.226

22-35 year###Step 1b###OM_Mean_T 2###.031###.110###.081###1###.776###1.032

###PM_Mean_T 2###-.105###.135###.603###1###.437###.900

###Constant###.414###.710###.341###1###.559###1.513

###EM_Mean_T 2###-.244###.287###.726###1###.394###.783

###IPC_Mean_T 2###.920###.201###21.034###1###.000###2.510

36-50 year###Step 1b###OM_Mean_T 2###-.072###.176###.166###1###.684###.931

###PM_Mean_T 2###-.410###.222###3.394###1###.065###.664

###Constant###.971###.967###1.009###1###.315###2.642

###EM_Mean_T 2###-1.723###.615###7.842###1###.005###.179

###IPC_Mean_T 2###1.134###.432###6.890###1###.009###3.107

51-60 year###Step 1b###OM_Mean_T 2###-.519###.383###1.833###1###.176###.595

###PM_Mean_T 2###-.151###.513###.086###1###.769###.860

###Constant###5.679###2.245###6.400###1###.011###292.521

###EM_Mean_T 2###.910###.742###1.506###1###.220###2.485

###IPC_Mean_T 2###.317###.562###.317###1###.573###1.373

61-70 year###Step 1b###OM_Mean_T 2###-.050###.491###.010###1###.919###.951

###PM_Mean_T 2###-.161###.644###.062###1###.803###.851

###Constant###-1.216###2.545###.228###1###.633###.297

Table 4.167 shows that for the age bracket 18-21 years, two independent variables interpersonal communication and print media made a significant impact on voting behavior, meanwhile the interpersonal communication put a positive impact (B=0.391, p<0.005) with an odd ratio 1.479. On the other hand, print media negatively impacted the voting behavior (B=-0.391, p<0.05) with an odd ratio 0.677.

For the age group 22-35 years, only interpersonal communication (IPC) had a highly significant, positive impact (B=0.800, p<0.0005) with odd ratio 2.226. Similarly, the age bracket 36-50 years, also positively influenced by IPC only (B=0.922, p<0.0005) with an odd ratio 2.510.

The age bracket 51-60 had been significantly influenced by two independent variables i.e. electronic media and interpersonal communication. IPC had a positive impact (B=1.134, p<0.005) with an odd ratio of 3.107, while electronic media (EM) had negative impact (B=-1,723, p<.0005) with an odd ratio 2.510.

Interestingly, the age bracket 60 year and above, did not significantly influenced by any means of communication

Table 4.8 Gender and Impact of communication channels on voting

Gender###B###S.E.###Wald###df###Sig.###Exp(B)

###EM_Mean_T 2###-.256###.173###2.195###1###.138###.774

###IPC_Mean_T 2###.668###.106###39.903###1###.000###1.949

Male###Step 1a###OM_Mean_T 2###-.006###.094###.004###1###.950###.994

###PM_Mean_T 2###-.257###.116###4.887###1###.027###.774

###Constant###.798###.600###1.770###1###.183###2.221

###EM_Mean_T 2###-.315###.169###3.486###1###.062###.729

###IPC_Mean_T 2###.714###.119###35.819###1###.000###2.041

Female###Step 1a###OM_Mean_T 2###-.100###.103###.940###1###.332###.905

###PM_Mean_T 2###-.351###.125###7.883###1###.005###.704

###Constant###1.303###.593###4.827###1###.028###3.681

Table 4.168 depicts that male and female both were significantly influenced by the interpersonal communication and print media, however, for male IPC positively influenced (B=.668, p<.0005) with an odd 1.949 and for female (B=.714, p< .0005) with an odd ratio of 2.041.

Print media negatively influenced voting behavior in male voters B=-.27, p<.05) with an off ratio of .774 and for female (B=-.351, p< .005) with an odd ratio off 0.704.

Table 4.12 Urban/Rural voters and Impact on Communication channels

Area###B###S.E.###Wald###Df Sig.###Exp(B)

###EM_Mean_Phase2###-.247 .168###2.160###1 .142###.781

###IPC_Mean_Phase2###.554 .106###27.375###1 .000###1.741

City###Step 1a###OM_Mean_Phase2###-.033 .093###.129###1 .720###.967

###PM_Mean_Phase2###-.361 .117###9.602###1 .002###.697

###Constant###1.369 .569###5.788###1 .016###3.931

###EM_Mean_Phase2###-.306 .172###3.169###1 .075###.737

###IPC_Mean_Phase2###.835 .119###49.128###1 .000###2.305

Village Step 1a###OM_Mean_Phase2###-.071 .104###.473###1 .491###.931

###PM_Mean_Phase2###-.234 .126###3.466###1 .063###.791

###Constant###.627 .634###.979###1 .322###1.872

Table 4.173 reflects that Interpersonal communication positively significantly impacted Urban voters decision (B=.554, p<.0005) with an odd ratio of 1.741 while print media (B=-.361, p<.005) negatively influenced them with odd ratios of .697. Rural voters were significantly positively influenced by IPC (B=.835, p<.0005) with an odd ratio of 2.305.

Table 4.13 Punjab Regions * Impact of communication channels

Region###B###S.E.###Wald###df Sig. Exp(B)

###EM_Mean_Phase2###-.616###.745###.683###1 .408###.540

###IPC_Mean_Phase2###1.633###.560###8.511###1 .004###5.119

Upper

###Step 1a###OM_Mean_Phase2###.145###.548###.070###1 .791###1.156

Punjab

###PM_Mean_Phase2###-.054###.471###.013###1 .909###.947

###Constant###-.696 2.542###.075###1 .784###.499

###EM_Mean_Phase2###-.531###.157###11.409###1 .001###.588

###IPC_Mean_Phase2###.589###.103###32.557###1 .000###1.801

Central

###Step 1a###OM_Mean_Phase2###-.089###.091###.954###1 .329###.915

Punjab

###PM_Mean_Phase2###-.040###.116###.120###1 .729###.961

###Constant###1.363###.572###5.666###1 .017###3.906

###EM_Mean_Phase2###.135###.194###.486###1 .486###1.144

###IPC_Mean_Phase2###.788###.130###36.913###1 .000###2.200

Southern

###Step 1a###OM_Mean_Phase2###.059###.114###.272###1 .602###1.061

Punjab

###PM_Mean_Phase2###-.655###.133###24.176###1 .000###.519

###Constant###.294###.676###.190###1 .663###1.342

Table 4.174 shows that interpersonal communication positively significantly impacted Upper Punjab voters decision (B=1.633, p<.005) with an odd ratio of 5.119. In Central Punjab electronic media (B=-.531, p<.005) negatively impacted voters with an odd ratio of .588 while IPC impacted positively (B=.589, p<.0005) with an odd ratio of 1.801.

In Southern Punjab IPC positively impacted (B=.788, p< .0005) with an odd ratio of 2.20 while print media negatively influenced (B=-.655, p<.0005) with an odd ratio of .519.

Overall, The study revealed that interpersonal communication (IPC) was the most powerful tool to impact the voters' decisions, electronic media (EM) second important while print media remained unable to significantly impact voters.

Notes and References

Ahmed, M. (2006). Voting behaviour in rural and urban areas of Punjab. Journal of Political Studies, 14, 45-56. Retrieved from http://pu.edu.pk/images/journal/pols/Currentissue pdf/voting%20behaviour.pdf

Bangash, A. H. (2013, May 5). Electronic media at crossroads. Daily Times. Retrieved from http://dailytimes.com.pk/opinion/05-May-13/electronic-media-at-crossroads

Pakistan Internet Use Stats (2016). Retrieved on October 12, 2016 from http://www.internetlivestats.com/internet-users/pakistan/

Panel study (1998). A Dictionary of Sociology. Retrieved November 26, 2016 from Encyclopedia.com: http://www.encyclopedia.com/social-sciences/dictionaries-thesauruses-pictures-and-press-releases/panel-study

Peshimam, G. (2013). Media-powered democracy: how media support has been pivotal to Pakistan's latest democratization project.Retrieved from https://reutersinstitute.politics.ox.ac.uk/

Rule, S. (2014). Encyclopedia of Quality of Life and Well-Being Research. (A. C. Michalos, Ed.) Dordrecht: Springer. Retrieved from https://link.springer.com/referenceworkentry/10.1007%2F978-94-007-0753-5_3181

Safdar, G., Shabir, G., Imran, M., andGhaznavi, Q. Z., (2015). The Role of Media in Increasing Turn-out in Election 2013:A Survey Study of Multan, Punjab, Pakistan. Pakistan Journal of Social Sciences (PJSS). Vol. 35, No. 1, pp. 411-424

Saleem, N., Hanan, M. A., and Tariq, T. (2015). Political Advertisements and Voters Behaviour in 2013 General Elections of Pakistan: Exposure vs Impact Analysis. Journal of the Research Society of Pakistan, 52(1).

Yaser N., Nawaz M., Paracha A.S. (2010). "Correlation Between Media`s Political Content and Voting Behavior: A case Study of 2008 election in Pakistan" Global Media Journal VOL-IV |ISSUE-I|
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